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mosaic_bayer.py
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mosaic_bayer.py
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import numpy as np
def mosaic_bayer(rgb, pattern='grbg', noiselevel=0):
num = np.zeros(len(pattern), dtype=int)
for i in range(len(pattern)):
if pattern[i] == 'r':
num[i] = 0
elif pattern[i] == 'g':
num[i] = 1
elif pattern[i] == 'b':
num[i] = 2
mosaic = np.zeros(rgb.shape)
mask = np.zeros(rgb.shape)
B = np.zeros(rgb.shape[:2])
rows1 = np.arange(0, rgb.shape[0], 2)
rows2 = np.arange(1, rgb.shape[0], 2)
cols1 = np.arange(0, rgb.shape[1], 2)
cols2 = np.arange(1, rgb.shape[1], 2)
B[rows1[:,None], cols1] = rgb[rows1[:,None], cols1, num[0]]
B[rows1[:,None], cols2] = rgb[rows1[:,None], cols2, num[1]]
B[rows2[:,None], cols1] = rgb[rows2[:,None], cols1, num[2]]
B[rows2[:,None], cols2] = rgb[rows2[:,None], cols2, num[3]]
np.random.seed(0)
B += noiselevel/255*np.random.randn(*B.shape)
mask[rows1[:,None], cols1, num[0]] = 1
mask[rows1[:,None], cols2, num[1]] = 1
mask[rows2[:,None], cols1, num[2]] = 1
mask[rows2[:,None], cols2, num[3]] = 1
mosaic[rows1[:,None], cols1, num[0]] = B[rows1[:,None], cols1]
mosaic[rows1[:,None], cols2, num[1]] = B[rows1[:,None], cols2]
mosaic[rows2[:,None], cols1, num[2]] = B[rows2[:,None], cols1]
mosaic[rows2[:,None], cols2, num[3]] = B[rows2[:,None], cols2]
return B, mosaic, mask