feat(v2): add multiple extra features from the pdf slides

backend/processing/algorithms.py

@@ -69,6 +69,16 @@ def histogram(image):
     return probabilities.round(8).tolist()
 
 
+def histogram_payload(image):
+    gray = to_gray(image)
+    payload = {"intensity": histogram(gray)}
+    if image.ndim == 3:
+        payload["r"] = (np.bincount(image[:, :, 0].ravel(), minlength=256).astype(np.float64) / image[:, :, 0].size).round(8).tolist()
+        payload["g"] = (np.bincount(image[:, :, 1].ravel(), minlength=256).astype(np.float64) / image[:, :, 1].size).round(8).tolist()
+        payload["b"] = (np.bincount(image[:, :, 2].ravel(), minlength=256).astype(np.float64) / image[:, :, 2].size).round(8).tolist()
+    return payload
+
+
 def image_to_data_url(image):
     pil_image = Image.fromarray(ensure_uint8(image))
     buffer = BytesIO()

backend/processing/migrations/0002_imagestate.py

@@ -0,0 +1,51 @@
+import django.db.models.deletion
+import uuid
+
+from django.db import migrations, models
+
+
+class Migration(migrations.Migration):
+    dependencies = [
+        ("processing", "0001_initial"),
+    ]
+
+    operations = [
+        migrations.CreateModel(
+            name="ImageState",
+            fields=[
+                ("id", models.UUIDField(default=uuid.uuid4, editable=False, primary_key=True, serialize=False)),
+                ("sequence", models.PositiveIntegerField(default=0)),
+                ("label", models.CharField(max_length=120)),
+                ("operation", models.CharField(max_length=96)),
+                ("params", models.JSONField(blank=True, default=dict)),
+                ("image", models.CharField(max_length=255)),
+                ("width", models.PositiveIntegerField()),
+                ("height", models.PositiveIntegerField()),
+                ("channels", models.PositiveSmallIntegerField()),
+                ("color_mode", models.CharField(max_length=16)),
+                ("histogram", models.JSONField(default=dict)),
+                ("created_at", models.DateTimeField(auto_now_add=True)),
+                (
+                    "parent",
+                    models.ForeignKey(
+                        blank=True,
+                        null=True,
+                        on_delete=django.db.models.deletion.SET_NULL,
+                        related_name="children",
+                        to="processing.imagestate",
+                    ),
+                ),
+                (
+                    "session",
+                    models.ForeignKey(
+                        on_delete=django.db.models.deletion.CASCADE,
+                        related_name="states",
+                        to="processing.imagesession",
+                    ),
+                ),
+            ],
+            options={
+                "ordering": ["sequence", "created_at"],
+            },
+        ),
+    ]

backend/processing/models.py

@@ -28,6 +28,26 @@ class ImageSession(models.Model):
         return timezone.now() >= self.expires_at
 
 
+class ImageState(models.Model):
+    id = models.UUIDField(primary_key=True, default=uuid.uuid4, editable=False)
+    session = models.ForeignKey(ImageSession, related_name="states", on_delete=models.CASCADE)
+    parent = models.ForeignKey("self", related_name="children", on_delete=models.SET_NULL, null=True, blank=True)
+    sequence = models.PositiveIntegerField(default=0)
+    label = models.CharField(max_length=120)
+    operation = models.CharField(max_length=96)
+    params = models.JSONField(default=dict, blank=True)
+    image = models.CharField(max_length=255)
+    width = models.PositiveIntegerField()
+    height = models.PositiveIntegerField()
+    channels = models.PositiveSmallIntegerField()
+    color_mode = models.CharField(max_length=16)
+    histogram = models.JSONField(default=dict)
+    created_at = models.DateTimeField(auto_now_add=True)
+
+    class Meta:
+        ordering = ["sequence", "created_at"]
+
+
 class ProcessingJob(models.Model):
     STATUS_PENDING = "pending"
     STATUS_RUNNING = "running"

backend/processing/registry.py

@@ -0,0 +1,342 @@
+import math
+
+import cv2
+import numpy as np
+
+from .algorithms import (
+    ProcessingError,
+    bit_plane,
+    box_filter,
+    contrast_stretch,
+    gamma,
+    gray_slice,
+    gray_to_color_sinusoidal,
+    gray_to_rgb,
+    histogram_equalization,
+    histogram_matching,
+    hsi_intensity_filter,
+    hsi_to_rgb,
+    logarithmic,
+    local_equalization,
+    negative,
+    normalize_to_uint8,
+    pseudo_color_slices,
+    rgb_to_hsi,
+    roberts,
+    sobel,
+    to_gray,
+    weighted_average,
+    median_filter,
+    high_boost,
+    ensure_uint8,
+)
+
+
+CH_BASIC = "Basic"
+CH3 = "Image Enhancement in the Spatial Domain"
+CH4 = "Image Enhancement in the Frequency Domain"
+CH6 = "Color Image Processing"
+
+
+def odd_param(default=3, max_value=35):
+    return {"type": "int", "default": default, "min": 3, "max": max_value, "step": 2, "odd": True}
+
+
+def float_param(default, min_value, max_value, step=0.1):
+    return {"type": "float", "default": default, "min": min_value, "max": max_value, "step": step}
+
+
+def int_param(default, min_value, max_value, step=1):
+    return {"type": "int", "default": default, "min": min_value, "max": max_value, "step": step}
+
+
+def select_param(default, choices):
+    return {"type": "select", "default": default, "choices": choices}
+
+
+def bool_param(default=False):
+    return {"type": "bool", "default": default}
+
+
+def crop(image, params):
+    x = max(0, int(params.get("x", 0)))
+    y = max(0, int(params.get("y", 0)))
+    width = int(params.get("width", image.shape[1] - x))
+    height = int(params.get("height", image.shape[0] - y))
+    if width <= 0 or height <= 0:
+        raise ProcessingError("Crop width and height must be positive.")
+    x2 = min(image.shape[1], x + width)
+    y2 = min(image.shape[0], y + height)
+    if x >= x2 or y >= y2:
+        raise ProcessingError("Crop rectangle is outside the image.")
+    return image[y:y2, x:x2]
+
+
+def identity(image, params):
+    return image.copy()
+
+
+def inverse_log(image, params):
+    c = float(params.get("c", 1.0))
+    normalized = image.astype(np.float32) / 255.0
+    transformed = np.expm1(normalized / max(c, 1e-8))
+    transformed /= max(float(np.max(transformed)), 1e-8)
+    return ensure_uint8(np.round(transformed * 255.0))
+
+
+def threshold(image, params):
+    level = int(params.get("level", 128))
+    high = int(params.get("high", 255))
+    low = int(params.get("low", 0))
+    gray = to_gray(image)
+    return gray_to_rgb(np.where(gray >= level, high, low).astype(np.uint8))
+
+
+def histeq(image, params):
+    mode = params.get("mode", "intensity")
+    if image.ndim == 2 or mode == "grayscale":
+        return histogram_equalization(image, params)
+    if mode == "rgb":
+        channels = [histogram_equalization(image[:, :, idx], params)[:, :, 0] for idx in range(3)]
+        return np.stack(channels, axis=2).astype(np.uint8)
+    hsi = rgb_to_hsi(image)
+    intensity = np.round(hsi[..., 2] * 255).astype(np.uint8)
+    hsi[..., 2] = histogram_equalization(intensity, params)[:, :, 0].astype(np.float32) / 255.0
+    return hsi_to_rgb(hsi)
+
+
+def gaussian_noise(image, params):
+    mean = float(params.get("mean", 0))
+    variance = float(params.get("variance", 0.01))
+    sigma = math.sqrt(max(variance, 0.0)) * 255.0
+    noise = np.random.default_rng().normal(mean * 255.0, sigma, size=image.shape)
+    return ensure_uint8(np.round(image.astype(np.float32) + noise))
+
+
+def salt_pepper_noise(image, params):
+    amount = float(params.get("amount", 0.03))
+    salt_ratio = float(params.get("salt_ratio", 0.5))
+    output = image.copy()
+    rng = np.random.default_rng()
+    mask = rng.random(image.shape[:2])
+    salt = mask < amount * salt_ratio
+    pepper = (mask >= amount * salt_ratio) & (mask < amount)
+    output[salt] = 255
+    output[pepper] = 0
+    return output
+
+
+def speckle_noise(image, params):
+    variance = float(params.get("variance", 0.04))
+    noise = np.random.default_rng().normal(0, math.sqrt(max(variance, 0.0)), size=image.shape)
+    return ensure_uint8(np.round(image.astype(np.float32) + image.astype(np.float32) * noise))
+
+
+def gaussian_filter(image, params):
+    size = int(params.get("size", 3))
+    variance = float(params.get("variance", 1.0))
+    if size < 3 or size % 2 == 0:
+        raise ProcessingError("size must be an odd integer >= 3.")
+    sigma = math.sqrt(max(variance, 1e-8))
+    return cv2.GaussianBlur(image, (size, size), sigmaX=sigma, sigmaY=sigma, borderType=cv2.BORDER_REFLECT)
+
+
+def max_filter(image, params):
+    size = int(params.get("size", 3))
+    if size < 3 or size % 2 == 0:
+        raise ProcessingError("size must be an odd integer >= 3.")
+    return cv2.dilate(image, np.ones((size, size), np.uint8))
+
+
+def min_filter(image, params):
+    size = int(params.get("size", 3))
+    if size < 3 or size % 2 == 0:
+        raise ProcessingError("size must be an odd integer >= 3.")
+    return cv2.erode(image, np.ones((size, size), np.uint8))
+
+
+def laplacian_slide(image, params):
+    mask_name = params.get("mask", "cross")
+    kernels = {
+        "cross": np.array([[0, 1, 0], [1, -5, 1], [0, 1, 0]], dtype=np.float32),
+        "diagonal": np.array([[1, 1, 1], [1, -9, 1], [1, 1, 1]], dtype=np.float32),
+        "zero_sum_cross": np.array([[0, 1, 0], [1, -4, 1], [0, 1, 0]], dtype=np.float32),
+        "zero_sum_diagonal": np.array([[1, 1, 1], [1, -8, 1], [1, 1, 1]], dtype=np.float32),
+    }
+    kernel = kernels.get(mask_name)
+    if kernel is None:
+        raise ProcessingError("Unknown Laplacian mask.")
+    channels = [cv2.filter2D(image[:, :, idx], cv2.CV_32F, kernel, borderType=cv2.BORDER_REFLECT) for idx in range(image.shape[2])]
+    result = np.stack(channels, axis=2)
+    return normalize_to_uint8(result) if params.get("mode", "sharpen") == "detail" else ensure_uint8(result)
+
+
+def gradient_abs_sum(image, params):
+    operator = params.get("operator", "sobel")
+    gray = to_gray(image).astype(np.float32)
+    if operator == "roberts":
+        gx = np.array([[-1, 0], [0, 1]], dtype=np.float32)
+        gy = np.array([[0, -1], [1, 0]], dtype=np.float32)
+    else:
+        gx = np.array([[-1, -2, -1], [0, 0, 0], [1, 2, 1]], dtype=np.float32)
+        gy = np.array([[-1, 0, 1], [-2, 0, 2], [-1, 0, 1]], dtype=np.float32)
+    fx = cv2.filter2D(gray, cv2.CV_32F, gx, borderType=cv2.BORDER_REFLECT)
+    fy = cv2.filter2D(gray, cv2.CV_32F, gy, borderType=cv2.BORDER_REFLECT)
+    return gray_to_rgb(normalize_to_uint8(np.abs(fx) + np.abs(fy)))
+
+
+def rgb_channel(image, params):
+    channel = params.get("channel", "r")
+    index = {"r": 0, "g": 1, "b": 2}.get(channel, 0)
+    return gray_to_rgb(image[:, :, index])
+
+
+def hsi_view(image, params):
+    component = params.get("component", "i")
+    hsi = rgb_to_hsi(image)
+    index = {"h": 0, "s": 1, "i": 2}.get(component, 2)
+    return gray_to_rgb(np.round(hsi[:, :, index] * 255.0).astype(np.uint8))
+
+
+def fft_spectrum(image, params):
+    gray = to_gray(image).astype(np.float32)
+    spectrum = np.fft.fftshift(np.fft.fft2(gray))
+    mode = params.get("mode", "log_magnitude")
+    if mode == "phase":
+        return gray_to_rgb(normalize_to_uint8(np.angle(spectrum)))
+    magnitude = np.abs(spectrum)
+    if mode == "log_magnitude":
+        magnitude = np.log1p(magnitude)
+    return gray_to_rgb(normalize_to_uint8(magnitude))
+
+
+def distance_grid(shape):
+    rows, cols = shape
+    u = np.arange(rows) - rows / 2
+    v = np.arange(cols) - cols / 2
+    vv, uu = np.meshgrid(v, u)
+    return np.sqrt(uu**2 + vv**2)
+
+
+def frequency_filter(image, params):
+    gray = to_gray(image).astype(np.float32)
+    d0 = float(params.get("cutoff", 40))
+    order = int(params.get("order", 2))
+    family = params.get("family", "gaussian")
+    kind = params.get("kind", "lowpass")
+    d = distance_grid(gray.shape)
+    if family == "ideal":
+        mask = (d <= d0).astype(np.float32)
+    elif family == "butterworth":
+        mask = 1.0 / (1.0 + (d / max(d0, 1e-8)) ** (2 * max(order, 1)))
+    else:
+        mask = np.exp(-(d**2) / (2.0 * max(d0, 1e-8) ** 2))
+    if kind == "highpass":
+        mask = 1.0 - mask
+    if params.get("output", "image") == "mask":
+        return gray_to_rgb(normalize_to_uint8(mask))
+    f = np.fft.fftshift(np.fft.fft2(gray))
+    result = np.real(np.fft.ifft2(np.fft.ifftshift(f * mask)))
+    return gray_to_rgb(normalize_to_uint8(result))
+
+
+def frequency_laplacian(image, params):
+    gray = to_gray(image).astype(np.float32)
+    rows, cols = gray.shape
+    u = np.arange(rows) - rows / 2
+    v = np.arange(cols) - cols / 2
+    vv, uu = np.meshgrid(v, u)
+    h = -4.0 * (np.pi**2) * (uu**2 + vv**2)
+    f = np.fft.fftshift(np.fft.fft2(gray))
+    result = np.real(np.fft.ifft2(np.fft.ifftshift(f * h)))
+    return gray_to_rgb(normalize_to_uint8(result))
+
+
+def correlation(image, params):
+    kernel = np.array(params.get("kernel", [[1, 1, 1], [1, 1, 1], [1, 1, 1]]), dtype=np.float32)
+    kernel /= max(float(np.sum(np.abs(kernel))), 1e-8)
+    gray = to_gray(image).astype(np.float32)
+    return gray_to_rgb(normalize_to_uint8(cv2.filter2D(gray, cv2.CV_32F, kernel, borderType=cv2.BORDER_REFLECT)))
+
+
+def convolution(image, params):
+    kernel = np.array(params.get("kernel", [[1, 1, 1], [1, 1, 1], [1, 1, 1]]), dtype=np.float32)
+    return correlation(image, {"kernel": np.flipud(np.fliplr(kernel)).tolist()})
+
+
+def bone_scan_workflow(image, params):
+    gray_rgb = gray_to_rgb(to_gray(image))
+    lap_detail = laplacian_slide(gray_rgb, {"mask": "zero_sum_diagonal", "mode": "detail"})
+    sharpened = ensure_uint8(gray_rgb.astype(np.float32) + lap_detail.astype(np.float32))
+    sobel_img = gradient_abs_sum(gray_rgb, {"operator": "sobel"})
+    smooth_sobel = box_filter(sobel_img, {"size": 5})
+    mask = normalize_to_uint8((sharpened.astype(np.float32) * smooth_sobel.astype(np.float32)) / 255.0)
+    summed = ensure_uint8(gray_rgb.astype(np.float32) + mask.astype(np.float32))
+    return gamma(summed, {"gamma": float(params.get("gamma", 0.5)), "c": 1.0})
+
+
+def operation(id, label, chapter, slide_group, func, params=None, supports="both"):
+    return {
+        "id": id,
+        "label": label,
+        "chapter": chapter,
+        "slide_group": slide_group,
+        "params": params or {},
+        "supports": supports,
+        "func": func,
+    }
+
+
+OPERATIONS = [
+    operation("crop", "Crop", CH_BASIC, "Workspace", crop, {"x": int_param(0, 0, 4000), "y": int_param(0, 0, 4000), "width": int_param(256, 1, 8000), "height": int_param(256, 1, 8000)}),
+    operation("identity", "Identity", CH3, "Point Processing", identity),
+    operation("negative", "Negative", CH3, "Point Processing", negative),
+    operation("log", "Log", CH3, "Point Processing", logarithmic, {"c": float_param(1.44, 0.1, 5, 0.05)}),
+    operation("inverse_log", "Inverse Log", CH3, "Point Processing", inverse_log, {"c": float_param(1.0, 0.1, 5, 0.05)}),
+    operation("gamma", "Power-Law / Gamma", CH3, "Point Processing", gamma, {"gamma": float_param(1.0, 0.1, 5, 0.05), "c": float_param(1.0, 0.1, 3, 0.05)}),
+    operation("threshold", "Thresholding", CH3, "Point Processing", threshold, {"level": int_param(128, 0, 255), "low": int_param(0, 0, 255), "high": int_param(255, 0, 255)}),
+    operation("contrast_stretch", "Contrast Stretching", CH3, "Piecewise Linear", contrast_stretch, {"low": int_param(30, 0, 254), "high": int_param(220, 1, 255)}),
+    operation("gray_slice", "Gray-Level Slicing", CH3, "Piecewise Linear", gray_slice, {"start": int_param(96, 0, 255), "end": int_param(160, 0, 255), "preserve_background": bool_param(True)}),
+    operation("bit_plane", "Bit-Plane Slicing", CH3, "Piecewise Linear", bit_plane, {"bit": int_param(7, 0, 7)}),
+    operation("histeq", "histeq()", CH3, "Histogram Processing", histeq, {"mode": select_param("intensity", ["intensity", "rgb", "grayscale"])}),
+    operation("hist_match", "Histogram Specification", CH3, "Histogram Processing", histogram_matching, {"target": select_param("uniform", ["uniform", "dark", "bright", "bimodal"])}),
+    operation("local_equalization", "Local Enhancement", CH3, "Histogram Processing", local_equalization, {"size": odd_param(7, 31)}),
+    operation("gaussian_noise", "Add Gaussian Noise", CH3, "Noise and Denoising", gaussian_noise, {"mean": float_param(0, -1, 1, 0.01), "variance": float_param(0.01, 0, 0.2, 0.005)}),
+    operation("salt_pepper_noise", "Add Salt & Pepper Noise", CH3, "Noise and Denoising", salt_pepper_noise, {"amount": float_param(0.03, 0, 0.5, 0.01), "salt_ratio": float_param(0.5, 0, 1, 0.05)}),
+    operation("speckle_noise", "Add Speckle Noise", CH3, "Noise and Denoising", speckle_noise, {"variance": float_param(0.04, 0, 0.3, 0.01)}),
+    operation("box_filter", "Box / Average Filter", CH3, "Smoothing Linear Filters", box_filter, {"size": odd_param(3, 35)}),
+    operation("weighted_average", "Weighted Average Filter", CH3, "Smoothing Linear Filters", weighted_average, {"size": odd_param(3, 35)}),
+    operation("gaussian_filter", "Gaussian fspecial Filter", CH3, "Smoothing Linear Filters", gaussian_filter, {"size": odd_param(3, 35), "variance": float_param(1.0, 0.01, 25, 0.1)}),
+    operation("median_filter", "Median Filter", CH3, "Order-Statistics Filters", median_filter, {"size": odd_param(3, 25)}),
+    operation("max_filter", "Max Filter", CH3, "Order-Statistics Filters", max_filter, {"size": odd_param(3, 25)}),
+    operation("min_filter", "Min Filter", CH3, "Order-Statistics Filters", min_filter, {"size": odd_param(3, 25)}),
+    operation("laplacian_slide", "Laplacian Masks", CH3, "Sharpening Spatial Filters", laplacian_slide, {"mask": select_param("cross", ["cross", "diagonal", "zero_sum_cross", "zero_sum_diagonal"]), "mode": select_param("sharpen", ["sharpen", "detail"])}),
+    operation("gradient_abs_sum", "Gradient abs(imfilter Gx)+abs(imfilter Gy)", CH3, "Gradient Operator", gradient_abs_sum, {"operator": select_param("sobel", ["sobel", "roberts"])}),
+    operation("sobel", "Sobel Magnitude", CH3, "Gradient Operator", sobel),
+    operation("roberts", "Roberts Magnitude", CH3, "Gradient Operator", roberts),
+    operation("high_boost", "High-Boost Filtering", CH3, "High-Boost Filtering", high_boost, {"amplification": float_param(1.5, 1, 6, 0.1), "size": odd_param(3, 35)}),
+    operation("bone_scan_workflow", "Bone Scan Workflow Preset", CH3, "Combining Spatial Enhancement Methods", bone_scan_workflow, {"gamma": float_param(0.5, 0.1, 2, 0.05)}),
+    operation("fft_spectrum", "FFT/DFT Spectrum View", CH4, "DFT and FFT", fft_spectrum, {"mode": select_param("log_magnitude", ["magnitude", "log_magnitude", "phase"])}),
+    operation("frequency_filter", "Ideal/Butterworth/Gaussian Frequency Filter", CH4, "Frequency Domain Filtering", frequency_filter, {"family": select_param("gaussian", ["ideal", "butterworth", "gaussian"]), "kind": select_param("lowpass", ["lowpass", "highpass"]), "cutoff": float_param(40, 1, 512, 1), "order": int_param(2, 1, 10), "output": select_param("image", ["image", "mask"])}),
+    operation("frequency_laplacian", "Laplacian in Frequency Domain", CH4, "Sharpening Highpass Filtering", frequency_laplacian),
+    operation("convolution", "Convolution Utility", CH4, "Convolution", convolution),
+    operation("correlation", "Correlation Utility", CH4, "Correlation", correlation),
+    operation("rgb_channel", "RGB Channel View", CH6, "RGB color model", rgb_channel, {"channel": select_param("r", ["r", "g", "b"])}),
+    operation("hsi_view", "HSI Component View", CH6, "HSI color model", hsi_view, {"component": select_param("i", ["h", "s", "i"])}),
+    operation("hsi_intensity_filter", "HSI Intensity Processing", CH6, "HSI color model", hsi_intensity_filter, {"method": select_param("smooth", ["smooth", "sharpen"]), "size": odd_param(3, 25)}),
+    operation("pseudo_color_slices", "Pseudocolor Intensity Slicing", CH6, "Pseudocolor Image Processing", pseudo_color_slices),
+    operation("gray_to_color_sinusoidal", "Gray-Level to Color Transform", CH6, "Gray level to color transformation", gray_to_color_sinusoidal, {"hue_frequency": float_param(1, 0.2, 4, 0.1), "saturation_frequency": float_param(0.5, 0.1, 4, 0.1), "intensity_frequency": float_param(0.25, 0.1, 4, 0.1)}),
+]
+
+OPERATION_MAP = {item["id"]: item for item in OPERATIONS}
+
+
+def operation_metadata():
+    return [{key: value for key, value in item.items() if key != "func"} for item in OPERATIONS]
+
+
+def apply_registered_operation(image, operation_id, params=None):
+    item = OPERATION_MAP.get(operation_id)
+    if item is None:
+        raise ProcessingError(f"Unsupported operation '{operation_id}'.")
+    return ensure_uint8(item["func"](ensure_uint8(image), params or {}))

backend/processing/selectors.py

@@ -1,4 +1,4 @@
-from .models import ImageSession, ProcessingJob
+from .models import ImageSession, ImageState, ProcessingJob
 
 
 def image_session_get(*, session_id):
@@ -7,3 +7,11 @@ def image_session_get(*, session_id):
 
 def processing_job_get(*, job_id):
     return ProcessingJob.objects.filter(id=job_id).first()
+
+
+def image_state_get(*, state_id):
+    return ImageState.objects.select_related("session", "parent").filter(id=state_id).first()
+
+
+def image_states_list(*, session_id):
+    return ImageState.objects.select_related("parent").filter(session_id=session_id).order_by("sequence", "created_at")

backend/processing/services.py

@@ -1,10 +1,12 @@
 import time
 
+import numpy as np
 from django.conf import settings
 from django.utils import timezone
 
-from .algorithms import ProcessingError, decode_image, histogram, process_image
+from .algorithms import ProcessingError, average_images, decode_image, histogram, histogram_payload, normalize_to_uint8, process_image, verify_registration
-from .models import ImageSession, ProcessingJob
+from .models import ImageSession, ImageState, ProcessingJob
+from .registry import apply_registered_operation
 from .storage import load_image_array, payload_for_image, save_image_array
 from .tasks import run_batch_job
 
@@ -25,19 +27,145 @@ def image_session_create(*, uploaded_file=None, image_base64=None):
         original_histogram=hist,
         expires_at=timezone.now() + timezone.timedelta(hours=settings.IMAGE_SESSION_TTL_HOURS),
     )
+    state = image_state_create(
+        session=session,
+        parent=None,
+        image=image,
+        operation="upload",
+        params={},
+        label="S0 Upload",
+        prefix="state-upload",
+    )
     payload = {
         "session_id": str(session.id),
+        "active_state_id": str(state.id),
         "width": session.width,
         "height": session.height,
         "channels": session.channels,
         "color_mode": session.color_mode,
         "original_histogram": hist,
+        "histogram": state.histogram,
         "expires_at": session.expires_at.isoformat(),
+        "states": [image_state_payload(state=state, include_image=True)],
     }
     payload.update(payload_for_image(image, relative_path))
     return payload
 
 
+def image_state_create(*, session, parent, image, operation, params, label=None, prefix="state"):
+    relative_path = save_image_array(image, prefix)
+    sequence = session.states.count()
+    state = ImageState.objects.create(
+        session=session,
+        parent=parent,
+        sequence=sequence,
+        label=label or f"S{sequence} {operation}",
+        operation=operation,
+        params=params or {},
+        image=relative_path,
+        width=image.shape[1],
+        height=image.shape[0],
+        channels=image.shape[2] if image.ndim == 3 else 1,
+        color_mode="RGB" if image.ndim == 3 else "L",
+        histogram=histogram_payload(image),
+    )
+    return state
+
+
+def image_state_payload(*, state, include_image=True):
+    payload = {
+        "state_id": str(state.id),
+        "session_id": str(state.session_id),
+        "parent_state_id": str(state.parent_id) if state.parent_id else None,
+        "sequence": state.sequence,
+        "label": state.label,
+        "operation": state.operation,
+        "params": state.params,
+        "width": state.width,
+        "height": state.height,
+        "channels": state.channels,
+        "color_mode": state.color_mode,
+        "histogram": state.histogram,
+        "created_at": state.created_at.isoformat(),
+    }
+    if include_image:
+        image = load_image_array(state.image)
+        payload.update(payload_for_image(image, state.image))
+    else:
+        payload["image_path"] = state.image
+        payload["image_url"] = f"{settings.MEDIA_URL}{state.image}"
+    return payload
+
+
+def image_states_payload(*, states):
+    return [image_state_payload(state=state, include_image=True) for state in states]
+
+
+def image_state_apply_operation(*, state, operation, params):
+    if state.session.expired:
+        raise ProcessingError("Image session has expired.")
+    source = load_image_array(state.image)
+    result = apply_registered_operation(source, operation, params or {})
+    new_state = image_state_create(
+        session=state.session,
+        parent=state,
+        image=result,
+        operation=operation,
+        params=params or {},
+        label=None,
+        prefix=f"state-{operation}",
+    )
+    return image_state_payload(state=new_state, include_image=True)
+
+
+def combine_states(*, states, operation, params=None):
+    params = params or {}
+    if len(states) < 2:
+        raise ProcessingError("At least two states are required.")
+    session = states[0].session
+    if any(state.session_id != session.id for state in states):
+        raise ProcessingError("All states must belong to the same session.")
+    images = [load_image_array(state.image) for state in states]
+    verify_registration(images)
+
+    if operation == "average":
+        result = average_images(images)
+    elif operation == "add":
+        result = np_clip_sum(images)
+    elif operation == "subtract":
+        result = normalize_to_uint8(images[0].astype("float32") - images[1].astype("float32"))
+    elif operation == "dot_product":
+        result = normalize_to_uint8(np.prod([image.astype("float32") / 255.0 for image in images], axis=0))
+    elif operation == "and":
+        result = images[0].copy()
+        for image in images[1:]:
+            result = result & image
+    elif operation == "or":
+        result = images[0].copy()
+        for image in images[1:]:
+            result = result | image
+    else:
+        raise ProcessingError(f"Unsupported combine operation '{operation}'.")
+
+    new_state = image_state_create(
+        session=session,
+        parent=states[0],
+        image=result,
+        operation=f"combine_{operation}",
+        params={**params, "state_ids": [str(state.id) for state in states]},
+        label=None,
+        prefix=f"state-combine-{operation}",
+    )
+    return image_state_payload(state=new_state, include_image=True)
+
+
+def np_clip_sum(images):
+    total = np.zeros_like(images[0], dtype="float32")
+    for image in images:
+        total += image.astype("float32")
+    return np.clip(total, 0, 255).astype("uint8")
+
+
 def image_session_process(*, session, operation, params):
     if session.expired:
         raise ProcessingError("Image session has expired.")

backend/processing/tasks.py

@@ -48,6 +48,8 @@ def cleanup_expired_sessions():
     for session in expired:
         delete_relative_file(session.original_image)
         delete_relative_file(session.processed_image)
+        for state in session.states.all():
+            delete_relative_file(state.image)
     expired.delete()
 
     old_jobs = ProcessingJob.objects.filter(created_at__lt=timezone.now() - timezone.timedelta(hours=24))

backend/processing/urls.py

@@ -1,11 +1,27 @@
 from django.urls import path
 
-from .views import BatchView, HealthView, ImageUploadView, JobDetailView, ProcessView
+from .views import (
+    BatchView,
+    HealthView,
+    ImageUploadView,
+    JobDetailView,
+    OperationsView,
+    ProcessView,
+    SessionStatesView,
+    StateCombineView,
+    StateHistogramView,
+    StateOperationView,
+)
 
 
 urlpatterns = [
     path("health/", HealthView.as_view(), name="health"),
     path("images/", ImageUploadView.as_view(), name="image-upload"),
+    path("operations/", OperationsView.as_view(), name="operations"),
+    path("sessions/<uuid:session_id>/states/", SessionStatesView.as_view(), name="session-states"),
+    path("states/<uuid:state_id>/operations/", StateOperationView.as_view(), name="state-operation"),
+    path("states/<uuid:state_id>/histogram/", StateHistogramView.as_view(), name="state-histogram"),
+    path("states/combine/", StateCombineView.as_view(), name="state-combine"),
     path("process/", ProcessView.as_view(), name="process"),
     path("batch/", BatchView.as_view(), name="batch"),
     path("jobs/<uuid:job_id>/", JobDetailView.as_view(), name="job-detail"),

backend/processing/views.py

@@ -3,8 +3,18 @@ from rest_framework.response import Response
 from rest_framework.views import APIView
 
 from .algorithms import ProcessingError
-from .selectors import image_session_get, processing_job_get
+from .registry import operation_metadata
-from .services import batch_job_create, image_session_create, image_session_process, processing_job_payload
+from .selectors import image_session_get, image_state_get, image_states_list, processing_job_get
+from .services import (
+    batch_job_create,
+    combine_states,
+    image_session_create,
+    image_session_process,
+    image_state_apply_operation,
+    image_state_payload,
+    image_states_payload,
+    processing_job_payload,
+)
 
 
 def error_response(message, code=status.HTTP_400_BAD_REQUEST):
@@ -59,6 +69,73 @@ class ProcessView(APIView):
             return error_response(str(exc), code)
 
 
+class OperationsView(APIView):
+    def get(self, request):
+        return Response({"operations": operation_metadata()})
+
+
+class SessionStatesView(APIView):
+    def get(self, request, session_id):
+        session = image_session_get(session_id=session_id)
+        if session is None:
+            return error_response("Image session does not exist.", status.HTTP_404_NOT_FOUND)
+        return Response({"session_id": str(session.id), "states": image_states_payload(states=image_states_list(session_id=session.id))})
+
+
+class StateOperationView(APIView):
+    class InputSerializer(serializers.Serializer):
+        operation = serializers.CharField()
+        params = serializers.DictField(required=False, default=dict)
+
+    def post(self, request, state_id):
+        serializer = self.InputSerializer(data=request.data)
+        serializer.is_valid(raise_exception=True)
+        state = image_state_get(state_id=state_id)
+        if state is None:
+            return error_response("Image state does not exist.", status.HTTP_404_NOT_FOUND)
+        try:
+            payload = image_state_apply_operation(
+                state=state,
+                operation=serializer.validated_data["operation"],
+                params=serializer.validated_data.get("params", {}),
+            )
+            return Response(payload, status=status.HTTP_201_CREATED)
+        except ProcessingError as exc:
+            code = status.HTTP_410_GONE if str(exc) == "Image session has expired." else status.HTTP_400_BAD_REQUEST
+            return error_response(str(exc), code)
+
+
+class StateCombineView(APIView):
+    class InputSerializer(serializers.Serializer):
+        operation = serializers.ChoiceField(choices=["add", "subtract", "dot_product", "average", "and", "or"])
+        state_ids = serializers.ListField(child=serializers.UUIDField(), min_length=2)
+        params = serializers.DictField(required=False, default=dict)
+
+    def post(self, request):
+        serializer = self.InputSerializer(data=request.data)
+        serializer.is_valid(raise_exception=True)
+        states = [image_state_get(state_id=state_id) for state_id in serializer.validated_data["state_ids"]]
+        if any(state is None for state in states):
+            return error_response("One or more image states do not exist.", status.HTTP_404_NOT_FOUND)
+        try:
+            payload = combine_states(
+                states=states,
+                operation=serializer.validated_data["operation"],
+                params=serializer.validated_data.get("params", {}),
+            )
+            return Response(payload, status=status.HTTP_201_CREATED)
+        except ProcessingError as exc:
+            return error_response(str(exc))
+
+
+class StateHistogramView(APIView):
+    def get(self, request, state_id):
+        state = image_state_get(state_id=state_id)
+        if state is None:
+            return error_response("Image state does not exist.", status.HTTP_404_NOT_FOUND)
+        return Response({"state_id": str(state.id), "histogram": state.histogram, "state": image_state_payload(state=state, include_image=False)})
+
+
 class BatchView(APIView):
     class InputSerializer(serializers.Serializer):
         operation = serializers.ChoiceField(choices=["average", "subtract"])

frontend/src/App.jsx

@@ -1,22 +1,50 @@
 import { useEffect, useMemo, useState } from "react";
-import CanvasPane from "./components/CanvasPane.jsx";
+import CanvasPane, { CanvasThumbnail } from "./components/CanvasPane.jsx";
 import Controls from "./components/Controls.jsx";
 import HistogramPanel from "./components/HistogramPanel.jsx";
-import { createBatch, getJob, processImage, uploadImage } from "./lib/api.js";
+import { applyStateOperation, combineStates, getOperations, listStates, uploadImage } from "./lib/api.js";
-import { useDebouncedEffect } from "./lib/debounce.js";
+
+function defaultCropParams(state) {
+  return {
+    x: 0,
+    y: 0,
+    width: state?.width || 256,
+    height: state?.height || 256
+  };
+}
 
 export default function App() {
   const [session, setSession] = useState(null);
-  const [processed, setProcessed] = useState(null);
+  const [states, setStates] = useState([]);
-  const [batchSessions, setBatchSessions] = useState([]);
+  const [activeState, setActiveState] = useState(null);
-  const [operation, setOperation] = useState("gamma");
+  const [operations, setOperations] = useState([]);
-  const [params, setParams] = useState({ gamma: 1 });
+  const [selectedOperation, setSelectedOperation] = useState("");
+  const [params, setParams] = useState({});
+  const [selectedStateIds, setSelectedStateIds] = useState([]);
   const [status, setStatus] = useState("Upload an image to begin.");
   const [busy, setBusy] = useState(false);
   const [transform, setTransform] = useState({ x: 0, y: 0, scale: 1 });
 
-  const originalHistogram = session?.original_histogram;
+  useEffect(() => {
-  const processedHistogram = processed?.processed_histogram || processed?.result_histogram;
+    getOperations()
+      .then((payload) => {
+        setOperations(payload.operations || []);
+        const first = payload.operations?.find((operation) => operation.id === "crop") || payload.operations?.[0];
+        if (first) {
+          setSelectedOperation(first.id);
+          setParams(Object.fromEntries(Object.entries(first.params || {}).map(([key, schema]) => [key, schema.default])));
+        }
+      })
+      .catch((error) => setStatus(error.message));
+  }, []);
+
+  async function refreshStates(sessionId, nextActiveId = null) {
+    const payload = await listStates(sessionId);
+    setStates(payload.states || []);
+    const nextActive = payload.states?.find((state) => state.state_id === nextActiveId) || payload.states?.at(-1) || null;
+    setActiveState(nextActive);
+    return nextActive;
+  }
 
   async function handleUpload(file) {
     if (!file) return;
@@ -25,10 +53,13 @@ export default function App() {
     try {
       const payload = await uploadImage(file);
       setSession(payload);
-      setProcessed(null);
+      const initialStates = payload.states || [];
-      setBatchSessions([payload.session_id]);
+      setStates(initialStates);
+      setActiveState(initialStates[0] || null);
+      setSelectedStateIds(initialStates[0] ? [initialStates[0].state_id] : []);
       setTransform({ x: 0, y: 0, scale: 1 });
-      setStatus(`${payload.width} x ${payload.height} ${payload.color_mode} image loaded.`);
+      setStatus(`${payload.width} x ${payload.height} ${payload.color_mode} image loaded as S0.`);
+      if (selectedOperation === "crop") setParams(defaultCropParams(initialStates[0]));
     } catch (error) {
       setStatus(error.message);
     } finally {
@@ -36,14 +67,24 @@ export default function App() {
     }
   }
 
-  async function handleBatchUpload(file) {
+  function handleSelectOperation(operationId, nextParams) {
-    if (!file) return;
+    setSelectedOperation(operationId);
+    setParams(operationId === "crop" ? { ...nextParams, ...defaultCropParams(activeState) } : nextParams);
+  }
+
+  function handleParamChange(key, value) {
+    setParams((current) => ({ ...current, [key]: value }));
+  }
+
+  async function handleApply() {
+    if (!activeState || !selectedOperation) return;
     setBusy(true);
-    setStatus("Uploading batch image...");
+    setStatus(`Applying ${selectedOperation} to ${activeState.label}...`);
     try {
-      const payload = await uploadImage(file);
+      const state = await applyStateOperation(activeState.state_id, selectedOperation, params);
-      setBatchSessions((current) => [...current, payload.session_id]);
+      await refreshStates(state.session_id, state.state_id);
-      setStatus("Batch image added.");
+      setSelectedStateIds([state.state_id]);
+      setStatus(`${state.label} created.`);
     } catch (error) {
       setStatus(error.message);
     } finally {
@@ -51,14 +92,15 @@ export default function App() {
     }
   }
 
-  async function runBatch(kind) {
+  async function handleCombine(kind) {
+    if (selectedStateIds.length < 2) return;
     setBusy(true);
-    setStatus(`Starting ${kind} job...`);
+    setStatus(`Combining ${selectedStateIds.length} states using ${kind}...`);
     try {
-      const job = await createBatch(kind, batchSessions);
+      const state = await combineStates(kind, selectedStateIds);
-      const result = await pollJob(job.job_id);
+      await refreshStates(state.session_id, state.state_id);
-      setProcessed(result);
+      setSelectedStateIds([state.state_id]);
-      setStatus(`${kind} complete.`);
+      setStatus(`${state.label} created.`);
     } catch (error) {
       setStatus(error.message);
     } finally {
@@ -66,86 +108,53 @@ export default function App() {
     }
   }
 
-  async function pollJob(jobId) {
+  function toggleCombineState(stateId) {
-    for (let attempt = 0; attempt < 80; attempt += 1) {
+    setSelectedStateIds((current) => current.includes(stateId) ? current.filter((id) => id !== stateId) : [...current, stateId]);
-      const job = await getJob(jobId);
-      setStatus(`Job ${job.status}: ${job.progress}%`);
-      if (job.status === "complete") return job;
-      if (job.status === "failed") throw new Error(job.error || "Batch job failed");
-      await new Promise((resolve) => window.setTimeout(resolve, 1000));
-    }
-    throw new Error("Batch job timed out.");
   }
 
-  useDebouncedEffect(
+  const originalState = states[0] || null;
-    () => {
-      if (!session?.session_id || !operation) return;
-      let cancelled = false;
-      async function run() {
-        setBusy(true);
-        setStatus(`Processing ${operation}...`);
-        try {
-          const payload = await processImage(session.session_id, operation, params);
-          if (!cancelled) {
-            setProcessed(payload);
-            setStatus(`${operation} complete in ${payload.elapsed_ms} ms.`);
-          }
-        } catch (error) {
-          if (!cancelled) setStatus(error.message);
-        } finally {
-          if (!cancelled) setBusy(false);
-        }
-      }
-      run();
-      return () => {
-        cancelled = true;
-      };
-    },
-    [session?.session_id, operation, JSON.stringify(params)],
-    300
-  );
-
-  const processedImage = processed?.image_data || session?.image_data;
-  const originalImage = session?.image_data;
-
   const viewportTitle = useMemo(() => {
-    if (!session) return "No image";
+    if (!activeState) return "No active state";
-    return `${session.width} x ${session.height} ${session.color_mode}`;
+    return `${activeState.label} · ${activeState.width} x ${activeState.height} ${activeState.color_mode}`;
-  }, [session]);
+  }, [activeState]);
 
   return (
     <div className="flex min-h-screen flex-col bg-zinc-950 text-zinc-100 lg:flex-row">
       <Controls
-        selected={operation}
+        operations={operations}
+        selectedOperation={selectedOperation}
         params={params}
-        onOperationChange={(nextOperation, nextParams) => {
+        states={states}
-          setOperation(nextOperation);
+        activeState={activeState}
-          setParams(nextParams);
+        selectedStateIds={selectedStateIds}
-        }}
-        onParamChange={(key, value) => setParams((current) => ({ ...current, [key]: value }))}
-        onUpload={handleUpload}
-        onBatchUpload={handleBatchUpload}
-        batchCount={batchSessions.length}
-        onBatchRun={runBatch}
-        disabled={!session || busy}
         busy={busy}
+        onUpload={handleUpload}
+        onSelectOperation={handleSelectOperation}
+        onParamChange={handleParamChange}
+        onApply={handleApply}
+        onSelectState={(state) => {
+          setActiveState(state);
+          if (selectedOperation === "crop") setParams(defaultCropParams(state));
+        }}
+        onToggleCombineState={toggleCombineState}
+        onCombine={handleCombine}
       />
 
       <main className="flex min-h-0 flex-1 flex-col">
         <header className="flex flex-wrap items-center justify-between gap-3 border-b border-zinc-800 bg-zinc-950 px-5 py-3">
           <div>
-            <p className="text-xs uppercase tracking-[0.18em] text-cyan-300">Professional Dark Studio</p>
+            <p className="text-xs uppercase tracking-[0.18em] text-cyan-300">Professor Slide Workspace</p>
             <h2 className="text-sm font-medium text-zinc-200">{viewportTitle}</h2>
           </div>
           <div className="text-sm text-zinc-400">{busy ? "Working..." : status}</div>
         </header>
 
-        <div className="grid min-h-0 flex-1 grid-cols-1 gap-px bg-zinc-800 lg:grid-cols-2">
+        <div className="relative min-h-0 flex-1 bg-zinc-800">
-          <CanvasPane title="Original" imageData={originalImage} histogram={originalHistogram} transform={transform} onTransform={setTransform} />
+          <CanvasThumbnail title="S0 Original" imageData={originalState?.image_data} />
-          <CanvasPane title="Processed" imageData={processedImage} histogram={processedHistogram} transform={transform} onTransform={setTransform} />
+          <CanvasPane title="Active State" imageData={activeState?.image_data} histogram={activeState?.histogram} transform={transform} onTransform={setTransform} />
         </div>
 
-        <HistogramPanel original={originalHistogram} processed={processedHistogram} />
+        <HistogramPanel original={originalState?.histogram} processed={activeState?.histogram} />
       </main>
     </div>
   );

frontend/src/App.real-render.test.jsx

@@ -1,9 +1,17 @@
 import { render, screen } from "@testing-library/react";
 import App from "./App.jsx";
 
+vi.mock("./lib/api.js", () => ({
+  getOperations: () => Promise.resolve({ operations: [] }),
+  listStates: () => Promise.resolve({ states: [] }),
+  uploadImage: vi.fn(),
+  applyStateOperation: vi.fn(),
+  combineStates: vi.fn()
+}));
+
 describe("App real render", () => {
   it("mounts without mocking third-party components", () => {
     render(<App />);
-    expect(screen.getByText("Spatial Image Enhancer Pro")).toBeInTheDocument();
+    expect(screen.getByText("Academic Image Processing Workspace")).toBeInTheDocument();
   });
 });

frontend/src/App.test.jsx

@@ -5,11 +5,19 @@ vi.mock("react-quick-pinch-zoom", () => ({
   default: ({ children }) => <div>{children}</div>
 }));
 
+vi.mock("./lib/api.js", () => ({
+  getOperations: () => Promise.resolve({ operations: [] }),
+  listStates: () => Promise.resolve({ states: [] }),
+  uploadImage: vi.fn(),
+  applyStateOperation: vi.fn(),
+  combineStates: vi.fn()
+}));
+
 describe("App", () => {
-  it("renders the processing studio immediately", () => {
+  it("renders the academic workspace immediately", () => {
     render(<App />);
-    expect(screen.getByText("Spatial Image Enhancer Pro")).toBeInTheDocument();
+    expect(screen.getByText("Academic Image Processing Workspace")).toBeInTheDocument();
-    expect(screen.getAllByText("Original").length).toBeGreaterThan(0);
+    expect(screen.getByText("Image States")).toBeInTheDocument();
-    expect(screen.getAllByText("Processed").length).toBeGreaterThan(0);
+    expect(screen.getByText("Combine Selected States")).toBeInTheDocument();
   });
 });

frontend/src/components/CanvasPane.jsx

@@ -47,3 +47,22 @@ export default function CanvasPane({ title, imageData, histogram, transform, onT
     </section>
   );
 }
+
+export function CanvasThumbnail({ title, imageData }) {
+  const canvasRef = useRef(null);
+
+  useEffect(() => {
+    drawToCanvas(canvasRef.current, imageData);
+  }, [imageData]);
+
+  if (!imageData) return null;
+
+  return (
+    <div className="absolute left-4 top-4 z-10 w-40 border border-zinc-700 bg-zinc-950/95 shadow-2xl shadow-black/50 md:w-52">
+      <div className="border-b border-zinc-800 px-3 py-2 text-xs font-semibold text-zinc-100">{title}</div>
+      <div className="max-h-40 overflow-hidden bg-black md:max-h-52">
+        <canvas ref={canvasRef} className="block h-auto w-full" />
+      </div>
+    </div>
+  );
+}

frontend/src/components/Controls.jsx

@@ -1,93 +1,111 @@
-import { Activity, Aperture, Blend, Layers, SlidersHorizontal, Upload } from "lucide-react";
+import { Combine, Crop, Layers, SlidersHorizontal, Upload } from "lucide-react";
 
-const groups = [
+function defaultParams(operation) {
-  {
+  return Object.fromEntries(
-    title: "Intensity",
+    Object.entries(operation?.params || {}).map(([key, schema]) => [key, schema.default])
-    icon: SlidersHorizontal,
+  );
-    operations: [
+}
-      { id: "negative", label: "Negative", params: [] },
+
-      { id: "log", label: "Log", params: [{ key: "c", label: "c", min: 0.1, max: 3, step: 0.05, default: 1.44 }] },
+function groupOperations(operations) {
-      { id: "gamma", label: "Gamma", params: [{ key: "gamma", label: "Gamma", min: 0.1, max: 4, step: 0.05, default: 1 }] },
+  return operations.reduce((acc, operation) => {
-      {
+    acc[operation.chapter] ||= {};
-        id: "contrast_stretch",
+    acc[operation.chapter][operation.slide_group] ||= [];
-        label: "Contrast Stretch",
+    acc[operation.chapter][operation.slide_group].push(operation);
-        params: [
+    return acc;
-          { key: "low", label: "Low", min: 0, max: 254, step: 1, default: 30 },
+  }, {});
-          { key: "high", label: "High", min: 1, max: 255, step: 1, default: 220 }
+}
-        ]
+
-      },
+function ParamControl({ name, schema, value, onChange }) {
-      {
+  if (schema.type === "select") {
-        id: "gray_slice",
+    return (
-        label: "Gray Slice",
+      <label className="mb-3 block text-xs text-zinc-300">
-        params: [
+        <span className="mb-1 block">{name}</span>
-          { key: "start", label: "Start", min: 0, max: 255, step: 1, default: 96 },
+        <select className="w-full border border-zinc-700 bg-zinc-950 px-2 py-2 text-sm" value={value ?? schema.default} onChange={(event) => onChange(name, event.target.value)}>
-          { key: "end", label: "End", min: 0, max: 255, step: 1, default: 160 }
+          {schema.choices.map((choice) => (
-        ]
+            <option key={choice} value={choice}>{choice}</option>
-      },
+          ))}
-      { id: "bit_plane", label: "Bit Plane", params: [{ key: "bit", label: "Bit", min: 0, max: 7, step: 1, default: 7 }] }
+        </select>
-    ]
+      </label>
-  },
+    );
-  {
-    title: "Histogram",
-    icon: Activity,
-    operations: [
-      { id: "hist_equalization", label: "Global Equalization", params: [] },
-      { id: "hist_match", label: "Match Uniform", params: [] },
-      { id: "local_equalization", label: "Local Equalization", params: [{ key: "size", label: "Window", min: 3, max: 31, step: 2, default: 7 }] }
-    ]
-  },
-  {
-    title: "Spatial Filters",
-    icon: Aperture,
-    operations: [
-      { id: "box_filter", label: "Box", params: [{ key: "size", label: "Size", min: 3, max: 35, step: 2, default: 3 }] },
-      { id: "weighted_average", label: "Weighted Avg", params: [{ key: "size", label: "Size", min: 3, max: 35, step: 2, default: 3 }] },
-      { id: "median_filter", label: "Median", params: [{ key: "size", label: "Size", min: 3, max: 15, step: 2, default: 3 }] },
-      { id: "laplacian", label: "Laplacian", params: [] },
-      {
-        id: "high_boost",
-        label: "High Boost",
-        params: [
-          { key: "amplification", label: "A", min: 1, max: 5, step: 0.1, default: 1.5 },
-          { key: "size", label: "Size", min: 3, max: 35, step: 2, default: 3 }
-        ]
-      },
-      { id: "sobel", label: "Sobel", params: [] },
-      { id: "roberts", label: "Roberts", params: [] }
-    ]
-  },
-  {
-    title: "Color",
-    icon: Blend,
-    operations: [
-      { id: "pseudo_color_slices", label: "Intensity Slices", params: [] },
-      { id: "gray_to_color_sinusoidal", label: "HSI Sinusoids", params: [{ key: "hue_frequency", label: "Hue Freq", min: 0.2, max: 4, step: 0.1, default: 1 }] },
-      { id: "hsi_intensity_filter", label: "HSI Smooth I", params: [{ key: "size", label: "Size", min: 3, max: 15, step: 2, default: 3 }] }
-    ]
   }
-];
+  if (schema.type === "bool") {
-
+    return (
-function initialParams(operation) {
+      <label className="mb-3 flex items-center gap-2 text-xs text-zinc-300">
-  return Object.fromEntries(operation.params.map((param) => [param.key, param.default]));
+        <input type="checkbox" checked={Boolean(value ?? schema.default)} onChange={(event) => onChange(name, event.target.checked)} />
+        {name}
+      </label>
+    );
+  }
+  return (
+    <label className="mb-4 block">
+      <div className="mb-2 flex items-center justify-between text-xs text-zinc-300">
+        <span>{name}{schema.odd ? " (odd)" : ""}</span>
+        <input
+          className="w-20 border border-zinc-700 bg-zinc-950 px-2 py-1 text-right tabular-nums"
+          type="number"
+          min={schema.min}
+          max={schema.max}
+          step={schema.step}
+          value={value ?? schema.default}
+          onChange={(event) => onChange(name, schema.type === "int" ? parseInt(event.target.value || schema.default, 10) : Number(event.target.value))}
+        />
+      </div>
+      <input
+        type="range"
+        min={schema.min}
+        max={schema.max}
+        step={schema.step}
+        value={value ?? schema.default}
+        onChange={(event) => onChange(name, schema.type === "int" ? parseInt(event.target.value, 10) : Number(event.target.value))}
+        className="w-full accent-cyan-400"
+      />
+    </label>
+  );
 }
 
 export default function Controls({
-  selected,
+  operations,
+  selectedOperation,
   params,
-  onOperationChange,
+  states,
-  onParamChange,
+  activeState,
+  selectedStateIds,
+  busy,
   onUpload,
-  onBatchUpload,
+  onSelectOperation,
-  batchCount,
+  onParamChange,
-  onBatchRun,
+  onApply,
-  disabled,
+  onSelectState,
-  busy
+  onToggleCombineState,
+  onCombine,
 }) {
+  const grouped = groupOperations(operations);
+  const operation = operations.find((item) => item.id === selectedOperation);
+
+  function renderParameterDrawer(item) {
+    if (selectedOperation !== item.id) return null;
+    return (
+      <div className="border border-emerald-700 bg-zinc-950 p-3">
+        <div className="mb-3 flex items-center gap-2 text-xs font-semibold uppercase tracking-[0.14em] text-emerald-300">
+          <SlidersHorizontal size={14} />
+          Parameters
+        </div>
+        {Object.entries(item.params || {}).map(([name, schema]) => (
+          <ParamControl key={name} name={name} schema={schema} value={params[name]} onChange={onParamChange} />
+        ))}
+        {Object.keys(item.params || {}).length === 0 ? <p className="mb-3 text-sm text-zinc-500">No parameters.</p> : null}
+        <button disabled={!activeState || busy} onClick={onApply} className="w-full border border-emerald-600 bg-emerald-950/60 px-3 py-2 text-sm font-semibold text-emerald-100 disabled:cursor-not-allowed disabled:opacity-40">
+          Apply to Active State
+        </button>
+      </div>
+    );
+  }
+
   return (
-    <aside className="flex h-full w-full flex-col border-r border-zinc-800 bg-zinc-950 lg:w-[360px]">
+    <aside className="flex h-full w-full flex-col border-r border-zinc-800 bg-zinc-950 lg:w-[430px]">
       <div className="border-b border-zinc-800 px-5 py-4">
-        <h1 className="text-lg font-semibold tracking-normal text-zinc-50">Spatial Image Enhancer Pro</h1>
+        <h1 className="text-lg font-semibold text-zinc-50">Academic Image Processing Workspace</h1>
-        <p className="mt-1 text-xs text-zinc-400">Vectorized spatial-domain processing studio</p>
+        <p className="mt-1 text-xs text-zinc-400">MATLAB-like states organized by lecture chapters</p>
       </div>
 
       <div className="space-y-3 border-b border-zinc-800 p-4">
@@ -96,72 +114,71 @@ export default function Controls({
           Upload Image
           <input type="file" accept="image/*" className="hidden" onChange={(event) => onUpload(event.target.files?.[0])} />
         </label>
-        <label className="flex cursor-pointer items-center justify-center gap-2 border border-zinc-700 bg-zinc-900 px-3 py-2 text-sm font-medium text-zinc-100 hover:bg-zinc-800">
-          <Layers size={16} />
-          Add Batch Image ({batchCount})
-          <input type="file" accept="image/*" className="hidden" onChange={(event) => onBatchUpload(event.target.files?.[0])} />
-        </label>
-        <div className="grid grid-cols-2 gap-2">
-          <button disabled={batchCount < 2 || busy} onClick={() => onBatchRun("average")} className="border border-zinc-700 bg-zinc-900 px-3 py-2 text-sm disabled:cursor-not-allowed disabled:opacity-40">
-            Average
-          </button>
-          <button disabled={batchCount < 2 || busy} onClick={() => onBatchRun("subtract")} className="border border-zinc-700 bg-zinc-900 px-3 py-2 text-sm disabled:cursor-not-allowed disabled:opacity-40">
-            Subtract
-          </button>
-        </div>
       </div>
 
+      <section className="border-b border-zinc-800 p-4">
+        <div className="mb-2 flex items-center gap-2 text-sm font-semibold text-zinc-100">
+          <Layers size={16} className="text-cyan-300" />
+          Image States
+        </div>
+        <div className="max-h-48 space-y-2 overflow-y-auto">
+          {states.length === 0 ? <p className="text-sm text-zinc-500">No states yet.</p> : states.map((state) => (
+            <div key={state.state_id} className={`flex items-center gap-2 border p-2 ${activeState?.state_id === state.state_id ? "border-emerald-500 bg-emerald-950/30" : "border-zinc-800 bg-zinc-900"}`}>
+              <input type="checkbox" checked={selectedStateIds.includes(state.state_id)} onChange={() => onToggleCombineState(state.state_id)} />
+              <button className="min-w-0 flex-1 text-left" onClick={() => onSelectState(state)}>
+                <div className="truncate text-sm text-zinc-100">{state.label}</div>
+                <div className="truncate text-xs text-zinc-500">{state.width}x{state.height} - {state.operation}</div>
+              </button>
+            </div>
+          ))}
+        </div>
+      </section>
+
+      <section className="border-b border-zinc-800 p-4">
+        <div className="mb-2 flex items-center gap-2 text-sm font-semibold text-zinc-100">
+          <Combine size={16} className="text-cyan-300" />
+          Combine Selected States
+        </div>
+        <div className="grid grid-cols-3 gap-2">
+          {["add", "subtract", "dot_product", "average", "and", "or"].map((kind) => (
+            <button key={kind} disabled={selectedStateIds.length < 2 || busy} onClick={() => onCombine(kind)} className="border border-zinc-700 bg-zinc-900 px-2 py-2 text-xs disabled:cursor-not-allowed disabled:opacity-40">
+              {kind}
+            </button>
+          ))}
+        </div>
+      </section>
+
       <div className="min-h-0 flex-1 overflow-y-auto p-4">
-        {groups.map((group) => {
+        {Object.entries(grouped).map(([chapter, groups]) => (
-          const Icon = group.icon;
+          <details key={chapter} open={chapter.includes("Chapter 3")} className="mb-3 border border-zinc-800 bg-zinc-900/60">
-          return (
+            <summary className="cursor-pointer px-3 py-3 text-sm font-semibold text-zinc-100">{chapter}</summary>
-            <details key={group.title} open className="mb-3 border border-zinc-800 bg-zinc-900/60">
+            <div className="space-y-3 border-t border-zinc-800 p-3">
-              <summary className="flex cursor-pointer list-none items-center gap-2 px-3 py-3 text-sm font-semibold text-zinc-100">
+              {Object.entries(groups).map(([slideGroup, items]) => (
-                <Icon size={16} className="text-cyan-300" />
+                <details key={slideGroup} className="border border-zinc-800 bg-zinc-950/70">
-                {group.title}
+                  <summary className="cursor-pointer px-3 py-2 text-xs font-semibold text-cyan-200">{slideGroup}</summary>
-              </summary>
+                  <div className="grid grid-cols-1 gap-2 p-2">
-              <div className="space-y-2 border-t border-zinc-800 p-3">
+                    {items.map((item) => (
-                {group.operations.map((operation) => (
+                      <div key={item.id} className="space-y-2">
-                  <button
+                        <button
-                    key={operation.id}
+                          disabled={!activeState || busy}
-                    disabled={disabled}
+                          onClick={() => onSelectOperation(item.id, defaultParams(item))}
-                    onClick={() => onOperationChange(operation.id, initialParams(operation))}
+                          className={`w-full border px-3 py-2 text-left text-sm ${selectedOperation === item.id ? "border-emerald-500 bg-emerald-950/50 text-emerald-100" : "border-zinc-700 bg-zinc-900 text-zinc-200 hover:bg-zinc-800"} disabled:cursor-not-allowed disabled:opacity-40`}
-                    className={`w-full border px-3 py-2 text-left text-sm transition ${
+                        >
-                      selected === operation.id ? "border-emerald-500 bg-emerald-950/50 text-emerald-100" : "border-zinc-700 bg-zinc-950 text-zinc-200 hover:bg-zinc-800"
+                          {item.id === "crop" ? <Crop size={14} className="mr-2 inline" /> : null}
-                    } disabled:cursor-not-allowed disabled:opacity-40`}
+                          {item.label}
-                  >
+                        </button>
-                    {operation.label}
+                        {renderParameterDrawer(item)}
-                  </button>
+                      </div>
-                ))}
+                    ))}
-              </div>
+                  </div>
-            </details>
+                </details>
-          );
+              ))}
-        })}
+            </div>
-
+          </details>
-        <div className="mt-4 border border-zinc-800 bg-zinc-900/60 p-3">
+        ))}
-          <h2 className="mb-3 text-sm font-semibold text-zinc-100">Parameters</h2>
-          {groups
-            .flatMap((group) => group.operations)
-            .find((operation) => operation.id === selected)
-            ?.params.map((param) => (
-              <label key={param.key} className="mb-4 block">
-                <div className="mb-2 flex items-center justify-between text-xs text-zinc-300">
-                  <span>{param.label}</span>
-                  <span className="tabular-nums text-zinc-400">{params[param.key] ?? param.default}</span>
-                </div>
-                <input
-                  type="range"
-                  min={param.min}
-                  max={param.max}
-                  step={param.step}
-                  value={params[param.key] ?? param.default}
-                  onChange={(event) => onParamChange(param.key, Number(event.target.value))}
-                  className="w-full accent-cyan-400"
-                />
-              </label>
-            )) || <p className="text-sm text-zinc-500">No tunable parameters for this operation.</p>}
-        </div>
       </div>
+
+      {operation ? null : <div className="border-t border-zinc-800 bg-zinc-950 p-4 text-sm text-zinc-500">Select an operation.</div>}
     </aside>
   );
 }

frontend/src/components/HistogramPanel.jsx

@@ -1,10 +1,23 @@
 import { Area, AreaChart, CartesianGrid, ResponsiveContainer, Tooltip, XAxis, YAxis } from "recharts";
 
+function seriesFrom(histogram, fallbackKey = "intensity") {
+  if (Array.isArray(histogram)) return histogram;
+  return histogram?.[fallbackKey] || histogram?.intensity || [];
+}
+
 function toChartData(original, processed) {
+  const originalSeries = seriesFrom(original);
+  const processedSeries = seriesFrom(processed);
+  const r = processed?.r || [];
+  const g = processed?.g || [];
+  const b = processed?.b || [];
   return Array.from({ length: 256 }, (_, level) => ({
     level,
-    original: original?.[level] ?? 0,
+    original: originalSeries?.[level] ?? 0,
-    processed: processed?.[level] ?? 0
+    processed: processedSeries?.[level] ?? 0,
+    r: r[level] ?? 0,
+    g: g[level] ?? 0,
+    b: b[level] ?? 0
   }));
 }
 
@@ -16,7 +29,7 @@ export default function HistogramPanel({ original, processed }) {
         <h2 className="text-sm font-semibold text-zinc-100">Histogram Analytics</h2>
         <div className="flex gap-3 text-xs text-zinc-400">
           <span className="text-cyan-300">Original</span>
-          <span className="text-emerald-300">Processed</span>
+          <span className="text-emerald-300">Active</span>
         </div>
       </div>
       <div className="h-40">
@@ -28,6 +41,9 @@ export default function HistogramPanel({ original, processed }) {
             <Tooltip contentStyle={{ background: "#18181b", border: "1px solid #3f3f46", color: "#f4f4f5" }} />
             <Area type="monotone" dataKey="original" stroke="#67e8f9" fill="#0891b2" fillOpacity={0.22} dot={false} />
             <Area type="monotone" dataKey="processed" stroke="#6ee7b7" fill="#059669" fillOpacity={0.24} dot={false} />
+            <Area type="monotone" dataKey="r" stroke="#f87171" fill="#ef4444" fillOpacity={0.08} dot={false} />
+            <Area type="monotone" dataKey="g" stroke="#4ade80" fill="#22c55e" fillOpacity={0.08} dot={false} />
+            <Area type="monotone" dataKey="b" stroke="#60a5fa" fill="#3b82f6" fillOpacity={0.08} dot={false} />
           </AreaChart>
         </ResponsiveContainer>
       </div>

frontend/src/lib/api.js

@@ -18,6 +18,39 @@ export async function uploadImage(file) {
   return parseResponse(response);
 }
 
+export async function getOperations() {
+  const response = await fetch(`${API_BASE}/api/operations/`);
+  return parseResponse(response);
+}
+
+export async function listStates(sessionId) {
+  const response = await fetch(`${API_BASE}/api/sessions/${sessionId}/states/`);
+  return parseResponse(response);
+}
+
+export async function applyStateOperation(stateId, operation, params = {}) {
+  const response = await fetch(`${API_BASE}/api/states/${stateId}/operations/`, {
+    method: "POST",
+    headers: { "Content-Type": "application/json" },
+    body: JSON.stringify({ operation, params })
+  });
+  return parseResponse(response);
+}
+
+export async function combineStates(operation, stateIds, params = {}) {
+  const response = await fetch(`${API_BASE}/api/states/combine/`, {
+    method: "POST",
+    headers: { "Content-Type": "application/json" },
+    body: JSON.stringify({ operation, state_ids: stateIds, params })
+  });
+  return parseResponse(response);
+}
+
+export async function getStateHistogram(stateId) {
+  const response = await fetch(`${API_BASE}/api/states/${stateId}/histogram/`);
+  return parseResponse(response);
+}
+
 export async function processImage(sessionId, operation, params) {
   const response = await fetch(`${API_BASE}/api/process/`, {
     method: "POST",