raw数据的排列方式(之一)如下图，GRGB；下面的代码将raw数据(dng格式)转成4通道的GGRB数据用于后续处理；

    image.png
    Bayer阵列

    1. import rawpy
    2. import scipy.io
    3. import cv2
    4. import numpy as np
    6. with rawpy.imread("3984_2984.dng") as raw:
    8.     # un-blur
    9.     # np_img = raw.postprocess(use_camera_wb=True, half_size=False, no_auto_bright=True, output_bps=8)
    10.     # scipy.misc.toimage(np_img, high=255, low=0, cmin=0, cmax=255).save("rgb.jpg")
    12.     print("===============================")
    13.     # print(raw.raw_value(9, 0))
    14.     raw_img = raw.raw_image  # get raw data
    15.     # print(raw_img)
    16.     raw_H = raw_img.shape[0]
    17.     raw_W = raw_img.shape[1]
    19.     if raw.raw_pattern[0, 0] == 0:                                 # CFA=RGGB
    20.         raw_G1 = raw_img[1:raw_H:2, 0:raw_W:2]
    21.         raw_G2 = raw_img[0:raw_H:2, 1:raw_W:2]
    22.         raw_R = raw_img[0:raw_H:2, 0:raw_W:2]
    23.         raw_B = raw_img[1:raw_H:2, 1:raw_W:2]
    24.     elif raw.raw_pattern[0, 0] == 2:                                # BGGR
    25.         raw_G1 = raw_img[1:raw_H:2, 0:raw_W:2]
    26.         raw_G2 = raw_img[0:raw_H:2, 1:raw_W:2]
    27.         raw_R = raw_img[1:raw_H:2, 1:raw_W:2]
    28.         raw_B = raw_img[0:raw_H:2, 0:raw_W:2]
    29.     elif raw.raw_pattern[0, 0] == 1 and raw.raw_pattern[0, 1] == 0:  # GRBG
    30.         raw_G1 = raw_img[0:raw_H:2, 0:raw_W:2]
    31.         raw_G2 = raw_img[1:raw_H:2, 1:raw_W:2]
    32.         raw_R = raw_img[1:raw_H:2, 0:raw_W:2]
    33.         raw_B = raw_img[0:raw_H:2, 0:raw_W:2]
    34.     elif raw.raw_pattern[0, 0] == 1 and raw.raw_pattern[0, 1] == 2:  # GBRG
    35.         raw_G1 = raw_img[0:raw_H:2, 0:raw_W:2]
    36.         raw_G2 = raw_img[1:raw_H:2, 1:raw_W:2]
    37.         raw_R = raw_img[1:raw_H:2, 0:raw_W:2]
    38.         raw_B = raw_img[0:raw_H:2, 1:raw_W:2]
    39.     else:
    40.         assert False
    42.     # blur
    43.     # blur_size = (15, 15)
    44.     # G1 = cv2.blur(raw_G1, blur_size)
    45.     # G2 = cv2.blur(raw_G2, blur_size)
    46.     # R = cv2.blur(raw_R, blur_size)
    47.     # B = cv2.blur(raw_B, blur_size)
    49.     print("==============================")
    50.     np_img = raw.postprocess(use_camera_wb=True, half_size=False, no_auto_bright=True, output_bps=8)
    51.     # save raw_img to rgb
    52.     scipy.misc.toimage(np_img, high=255, low=0, cmin=0, cmax=255).save("blur_rgb.jpg")