Python OpenCV和MATLAB之间的不同颜色结果

我使用Python 3.5.2与OpenCV 3.1.0和MATLAB R2016a.

RGB2YIQ的Python代码：

import cv2 as cv
import numpy as np

def rgb2yiq(img):
   row,col,ch = img.shape
   Y = np.zeros((row,col))
   I = np.zeros((row,col))
   Q = np.zeros((row,col))
   for i in range(row):
      for j in range(col):
         Y[i,j] = 0.299 * img[i,j,2] + 0.587 * img[i,1] + 0.114 * img[i,0]
         I[i,j] = 0.596 * img[i,2] - 0.274 * img[i,1] - 0.322 * img[i,0]
         Q[i,j] = 0.211 * img[i,2] - 0.523 * img[i,1] + 0.312 * img[i,0]
   yiq = cv.merge((Y,I,Q))
   return yiq.astype(np.uint8)

def main():
   img = cv.imread("C:/Users/Kadek/Documents/MATLAB/peppers.jpg")
   img = rgb2yiq(img)
   cv.imwrite("YIQ.jpg",img)
   cv.namedWindow('Image',cv.WINDOW_NORMAL)
   cv.imshow('Image',img)
   cv.waitKey(0)
   cv.destroyAllWindows()

main()

RGB2YIQ的MATLAB代码：

img = imread('peppers.jpg');
[row col ch] = size(img);

for x=1:row
  for y=1:col
      Y(x,y) = 0.299 * img(x,y,1) + 0.587 * img(x,2) + 0.114 * img(x,3);
      I(x,y) = 0.596 * img(x,1) - 0.274 * img(x,2) - 0.322 * img(x,3);
      Q(x,y) = 0.211 * img(x,1) - 0.523 * img(x,2) + 0.312 * img(x,3);
  end
end

yiq(:,:,1) = Y;
yiq(:,2) = I;
yiq(:,3) = Q;

figure,imshow(yiq);

Result for RGB2YIQ

YIQ2RGB的Python代码：

import cv2 as cv
import numpy as np

def yiq2rgb(img):
   row,ch = img.shape
   r = np.zeros((row,col))
   g = np.zeros((row,col))
   b = np.zeros((row,col))
   for i in range(row):
      for j in range(col):
         r[i,j] = img[i,0] * 1.0 + img[i,1] * 0.9562 + img[i,2] * 0.6214
         g[i,0] * 1.0 - img[i,1] * 0.2727 - img[i,2] * 0.6468
         b[i,1] * 1.1037 + img[i,2] * 1.7006
   rgb = cv.merge((b,g,r))
   return rgb.astype(np.uint8)

def main():
   img = cv.imread("YIQ.jpg")
   img = yiq2rgb(img)
   cv.imwrite("test.jpg",img)
   cv.waitKey(0)
   cv.destroyAllWindows()

main()

YIQ2RGB的MATLAB代码：

img = imread('YIQ.jpg');
[row col ch] = size(img);

for x=1:row
  for y=1:col
      R(x,y) = 1.0 * img(x,1) + 0.9562 * img(x,2) + 0.6214 * img(x,3);
      G(x,1) - 0.2727 * img(x,2) - 0.6468 * img(x,3);
      B(x,1) - 1.1037 * img(x,2) + 1.7006 * img(x,3);
  end
end

rgb(:,1) = R;
rgb(:,2) = G;
rgb(:,3) = B;

imwrite(rgb,'YIQ2RGB.jpg');

figure,imshow(rgb);

Result for YIQ2RGB

有人说我曾经在操作之前将图像转换为float64.已经尝试过,但没有改变.
我还使用astype(np.uint8)将float64转换为uint8以避免[0..255]之外的值.在MATLAB中没有这样的问题.