Code source added

src/methods/laurensi/reconstruct.py

+"""The main file for the reconstruction.
+This file should NOT be modified except the body of the 'run_reconstruction' function.
+Students can call their functions (declared in others files of src/methods/your_name).
+"""
+
+
+import numpy as np
+
+from src.forward_model import CFA
+from scipy.signal import medfilt2d
+
+
+def freeman_median_demosaicking(op: CFA, y: np.ndarray) -> np.ndarray:
+    """Performs the Freeman's method with median for demosaicking.
+
+    Args:
+        op (CFA): CFA operator.
+        y (np.ndarray): Mosaicked image.
+
+    Returns:
+        np.ndarray: Demosaicked image.
+    """
+    z = op.adjoint(y)
+    res = np.empty(op.input_shape)
+
+    mask_r = np.zeros_like(z[:, :, 0], dtype = float)
+    mask_g = np.zeros_like(z[:, :, 1], dtype = float)
+    mask_b = np.zeros_like(z[:, :, 2], dtype = float)
+
+    D_rg = z[:, :, 0] - z[:, :, 1]
+    M1 = medfilt2d(D_rg, kernel_size=5)
+
+    D_gb = z[:, :, 1] - z[:, :, 2]
+    M2 = medfilt2d(D_gb, kernel_size=5)
+
+    D_rb = z[:, :, 0] - z[:, :, 2]
+    M3 = medfilt2d(D_rb, kernel_size=5)
+
+    res[:, :, 0] = z[:, :, 0] + (M1 * mask_g + z[:, :, 1]) + (M3 * mask_b + z[:, :, 2])
+    res[:, :, 1] = z[:, :, 1] + (z[:, :, 0] - M1 * mask_r) + (M2 * mask_b + z[:, :, 2])
+    res[:, :, 2] = z[:, :, 2] + (z[:, :, 1] - M2 * mask_g) + (z[:, :, 0] - M3 * mask_r)
+
+    return res
+
+
+
+def run_reconstruction(y: np.ndarray, cfa: str) -> np.ndarray:
+    """Performs demosaicking on y.
+
+    Args:
+        y (np.ndarray): Mosaicked image to be reconstructed.
+        cfa (str): Name of the CFA. Can be bayer or quad_bayer.
+
+    Returns:
+        np.ndarray: Demosaicked image.
+    """
+    input_shape = (y.shape[0], y.shape[1], 3)
+    op = CFA(cfa, input_shape)
+
+    res = freeman_median_demosaicking(op, y)
+
+    return res
+
+
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+
+# 2023
+# Authors: Mauro Dalla Mura and Matthieu Muller