diff --git a/src/methods/chaari_mohamed/fonctions.ipynb b/src/methods/chaari_mohamed/fonctions.ipynb
new file mode 100644
index 0000000000000000000000000000000000000000..c94e976282662746f97d5eed762f16acbf3c824b
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+++ b/src/methods/chaari_mohamed/fonctions.ipynb
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+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 24,
+ "id": "ec6da321",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import numpy as np\n",
+ "from scipy.signal import convolve2d\n",
+ "from src.forward_model import CFA\n",
+ "\n",
+ "def bilinear_demosaicing(op: CFA, y: np.ndarray) -> np.ndarray:\n",
+ " \"\"\"\n",
+ " Bilinear demosaicing method.\n",
+ "\n",
+ " Args:\n",
+ " op (CFA): CFA operator.\n",
+ " y (np.ndarray): Mosaicked image.\n",
+ "\n",
+ " Returns:\n",
+ " np.ndarray: Demosaicked image.\n",
+ " \"\"\"\n",
+ " # Copie des valeurs directement connues pour chaque canal\n",
+ " red = y[:, :, 0]\n",
+ " green = y[:, :, 1]\n",
+ " blue = y[:, :, 2]\n",
+ "\n",
+ " # Création des masques pour chaque couleur selon le motif CFA\n",
+ " mask_red = (op.mask == 0) # Supposons que 0 correspond au rouge dans le masque\n",
+ " mask_green = (op.mask == 1) # Supposons que 1 correspond au vert\n",
+ " mask_blue = (op.mask == 2) # Supposons que 2 correspond au bleu\n",
+ "\n",
+ " # Interpolation bilinéaire pour le rouge et le bleu\n",
+ " # Note: np.multiply multiplie les éléments correspondants des tableaux, c'est pourquoi nous utilisons np.multiply au lieu de *\n",
+ " red_interp = convolve2d(np.multiply(red, mask_red), [[1/4, 1/2, 1/4], [1/2, 1, 1/2], [1/4, 1/2, 1/4]], mode='same')\n",
+ " blue_interp = convolve2d(np.multiply(blue, mask_blue), [[1/4, 1/2, 1/4], [1/2, 1, 1/2], [1/4, 1/2, 1/4]], mode='same')\n",
+ "\n",
+ " # Interpolation bilinéaire pour le vert\n",
+ " # Pour le vert, nous utilisons un autre noyau car il y a plus de pixels verts\n",
+ " green_interp = convolve2d(np.multiply(green, mask_green), [[0, 1/4, 0], [1/4, 1, 1/4], [0, 1/4, 0]], mode='same')\n",
+ "\n",
+ " # Création de l'image interpolée\n",
+ " demosaicked_image = np.stack((red_interp, green_interp, blue_interp), axis=-1)\n",
+ "\n",
+ " # Correction des valeurs interpolées: on réapplique les valeurs connues pour éviter le flou\n",
+ " demosaicked_image[:, :, 0][mask_red] = red[mask_red]\n",
+ " demosaicked_image[:, :, 1][mask_green] = green[mask_green]\n",
+ " demosaicked_image[:, :, 2][mask_blue] = blue[mask_blue]\n",
+ "\n",
+ " # Clip pour s'assurer que toutes les valeurs sont dans la plage [0, 1]\n",
+ " demosaicked_image = np.clip(demosaicked_image, 0, 1)\n",
+ "\n",
+ " return demosaicked_image\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 25,
+ "id": "cf379598",
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "def quad_bayer_demosaicing(op: CFA, y: np.ndarray) -> np.ndarray:\n",
+ " \"\"\"\n",
+ " Demosaicing method for Quad Bayer CFA pattern.\n",
+ "\n",
+ " Args:\n",
+ " op (CFA): CFA operator.\n",
+ " y (np.ndarray): Mosaicked image.\n",
+ "\n",
+ " Returns:\n",
+ " np.ndarray: Demosaicked image.\n",
+ " \"\"\"\n",
+ " \n",
+ " # Interpolation bilinéaire pour chaque canal\n",
+ " red_interp = convolve2d(np.multiply(y[:, :, 0], op.mask == 0), [[1/4, 1/2, 1/4], [1/2, 1, 1/2], [1/4, 1/2, 1/4]], mode='same')\n",
+ " green_interp = convolve2d(np.multiply(y[:, :, 1], op.mask == 1), [[0, 1/4, 0], [1/4, 1, 1/4], [0, 1/4, 0]], mode='same')\n",
+ " blue_interp = convolve2d(np.multiply(y[:, :, 2], op.mask == 2), [[1/4, 1/2, 1/4], [1/2, 1, 1/2], [1/4, 1/2, 1/4]], mode='same')\n",
+ "\n",
+ " # Assemblage de l'image interpolée\n",
+ " demosaicked_image = np.stack((red_interp, green_interp, blue_interp), axis=-1)\n",
+ "\n",
+ " # Réapplication des valeurs connues\n",
+ " demosaicked_image[:, :, 0][op.mask == 0] = y[:, :, 0][op.mask == 0]\n",
+ " demosaicked_image[:, :, 1][op.mask == 1] = y[:, :, 1][op.mask == 1]\n",
+ " demosaicked_image[:, :, 2][op.mask == 2] = y[:, :, 2][op.mask == 2]\n",
+ "\n",
+ " # Clip des valeurs pour les maintenir dans la plage appropriée\n",
+ " demosaicked_image = np.clip(demosaicked_image, 0, 1)\n",
+ "\n",
+ " return demosaicked_image\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 26,
+ "id": "3eec062c",
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "a6630396",
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ },
+ {
+ "cell_type": "code",
+ "execution_count": null,
+ "id": "ef4e59c8",
+ "metadata": {},
+ "outputs": [],
+ "source": []
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "Python 3 (ipykernel)",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.9.16"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/src/methods/chaari_mohamed/reconstruct.py b/src/methods/chaari_mohamed/reconstruct.py
new file mode 100644
index 0000000000000000000000000000000000000000..6f202941e0ece681f2a70397380409d476ae3e4c
--- /dev/null
+++ b/src/methods/chaari_mohamed/reconstruct.py
@@ -0,0 +1,61 @@
+"""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 src.methods.chaari_mohamed.fonctions import bilinear_demosaicing,quad_bayer_demosaicing
+
+
+def run_reconstruction(y: np.ndarray, cfa: str) -> np.ndarray:
+ """
+ Performs demosaicking on y based on the CFA pattern.
+
+ Args:
+ y (np.ndarray): Mosaicked image to be reconstructed.
+ cfa (str): Name of the CFA pattern. 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)
+
+ if cfa == 'bayer':
+ res = bilinear_demosaicing(op, y)
+ elif cfa == 'quad_bayer':
+ res = quad_bayer_demosaicing(op, y)
+ else:
+ raise ValueError("Unsupported CFA pattern. Supported patterns are 'bayer' and 'quad_bayer'.")
+
+ return res
+
+
+####
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+
+# 2023
+# Authors: Mauro Dalla Mura and Matthieu Muller
diff --git a/src/methods/chaari_mohamed/report_mohamed chaari.pdf b/src/methods/chaari_mohamed/report_mohamed chaari.pdf
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Binary files /dev/null and b/src/methods/chaari_mohamed/report_mohamed chaari.pdf differ