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Commit ed4368ba authored by Patrick Dai's avatar Patrick Dai
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import numpy as np
from scipy.signal import convolve2d
from src.forward_model import CFA
def naive_interpolation(op: CFA, y: np.ndarray) -> np.ndarray:
"""Performs a simple interpolation of the lost pixels.
Args:
op (CFA): CFA operator.
y (np.ndarray): Mosaicked image.
Returns:
np.ndarray: Demosaicked image.
"""
res = np.empty(op.input_shape)
z = op.adjoint(y)
res[:, :, 0] = convolve2d(z[:, :, 0], ker_bayer_red_blue, mode='same')
res[:, :, 1] = convolve2d(z[:, :, 1], ker_bayer_green, mode='same')
res[:, :, 2] = convolve2d(z[:, :, 2], ker_bayer_red_blue, mode='same')
return res
def Spectral_difference(op,y):
z = op.adjoint(y)
y_hat = naive_interpolation(op,y)
res = np.empty(op.input_shape)
for l in range(3):
res[:,:,0]+=z[:,:,l]+convolve2d(z[:,:,0]-y_hat[:,:,l]*op.mask[:,:,0], ker_bayer_red_blue, mode='same')*op.mask[:,:,l]
res[:,:,1]+=z[:,:,l]+convolve2d(z[:,:,1]-y_hat[:,:,l]*op.mask[:,:,1], ker_bayer_green, mode='same')*op.mask[:,:,l]
res[:,:,2]+=z[:,:,l]+convolve2d(z[:,:,2]-y_hat[:,:,l]*op.mask[:,:,2], ker_bayer_red_blue, mode='same')*op.mask[:,:,l]
return res
def quad_bayer_to_bayer(y_quad):
y_bayer=np.copy(y_quad)
for i in range(1,y_quad.shape[0],4):
temp = np.copy(y_bayer[i,:])
y_bayer[i,:]=y_bayer[i+1,:]
y_bayer[i+1,:]=temp
for j in range(1,y_quad.shape[1],4):
temp = np.copy(y_bayer[:,j])
y_bayer[:,j]=y_bayer[:,j+1]
y_bayer[:,j+1]=temp
return y_bayer
ker_bayer_red_blue = np.array([[1, 2, 1], [2, 4, 2], [1, 2, 1]]) / 4
ker_bayer_green = np.array([[0, 1, 0], [1, 4, 1], [0, 1, 0]]) / 4
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"""The main file for the baseline reconstruction.
This file should NOT be modified.
"""
import numpy as np
from src.forward_model import CFA
from src.methods.dai.function import Spectral_difference, quad_bayer_to_bayer
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)
if op.cfa == 'bayer':
res = Spectral_difference(op, y)
else:
op.mask = quad_bayer_to_bayer(op.mask)
res = Spectral_difference(CFA('bayer',input_shape),quad_bayer_to_bayer(y))
return res
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# 2023
# Authors: Mauro Dalla Mura and Matthieu Muller
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