def recover_blue(image_remove_blue):
RG_matrix, RG_record_matrix, RB_matrix, RB_record_matrix, GB_matrix, GB_record_matrix = csv_operation.import_csv(
)
image_recover_blue = copy.deepcopy(image_remove_blue)
image_size = image_remove_blue.shape
# num_channel = image_size[2]
num_row = image_size[0] # how many rows
num_column = image_size[1] # how many columns
# initialize recoverd_red to store
recovered_blue = np.zeros((num_row, num_column), dtype=np.int32)
# for now, we recover the image except edge
for i in np.arange(1, num_row - 1):
for j in np.arange(1, num_column - 1):
red_value = image_recover_blue[i, j, 0]
green_value = image_recover_blue[i, j, 1]
red_contrast = pixel_operation.rms_contrast(
image_recover_blue, i, j, 0)
green_contrast = pixel_operation.rms_contrast(
image_recover_blue, i, j, 1)
red_green_contrast_mean = (red_contrast + green_contrast) / 2
RG_matrix_index = pixel_operation.contrast_index(
red_green_contrast_mean)
recovered_blue[i, j] = RG_matrix[green_value, red_value,
RG_matrix_index]
image_recover_blue[:, :, 2] = recovered_blue
plt.imshow(image_recover_blue)
plt.xticks([])
plt.yticks([])
return image_recover_blue
def recover_red(image_remove_red):
RG_matrix, RG_record_matrix, RB_matrix, RB_record_matrix, GB_matrix, GB_record_matrix = csv_operation.import_csv(
)
image_recover_red = copy.deepcopy(image_remove_red)
image_size = image_remove_red.shape
# num_channel = image_size[2]
num_row = image_size[0] # how many rows
num_column = image_size[1] # how many columns
# initialize recoverd_red to store
recovered_red = np.zeros((num_row, num_column), dtype=np.int32)
# for now, we recover the image except edge
for i in np.arange(1, num_row - 1):
for j in np.arange(1, num_column - 1):
green_value = image_remove_red[i, j, 1]
blue_value = image_remove_red[i, j, 2]
green_contrast = pixel_operation.rms_contrast(
image_remove_red, i, j, 1)
blue_contrast = pixel_operation.rms_contrast(
image_remove_red, i, j, 2)
green_blue_contrast_mean = (green_contrast + blue_contrast) / 2
GB_matrix_index = pixel_operation.contrast_index(
green_blue_contrast_mean)
recovered_red[i, j] = GB_matrix[blue_value, green_value,
GB_matrix_index]
image_recover_red[:, :, 0] = recovered_red
plt.imshow(image_recover_red)
plt.xticks([])
plt.yticks([])
return image_recover_red