问题描述
我有一个彩色图像，表示为OpenCV Mat对象（C ++，图像类型CV_32FC3）。我有一个颜色校正矩阵，我想应用于RGB彩色图像的每个像素（或使用OpenCV约定的BGR，这里无关紧要）。色彩校正矩阵为3x3。
I have a color image represented as an OpenCV Mat object (C++, image type CV_32FC3). I have a color correction matrix that I want to apply to each pixel of the RGB color image (or BGR using OpenCV convention, doesn't matter here). The color correction matrix is 3x3.
我可以轻松迭代像素并创建一个代表RGB的矢量v（3x1），然后计算M * v，但这对我的实际来说太慢了时间视频应用程序。
I could easily iterate over the pixels and create a vector v (3x1) representing RGB, and then compute M*v, but this would be too slow for my real-time video application.
cv :: cvtColor函数很快，但似乎不允许自定义颜色转换。
The cv::cvtColor function is fast, but does not seem to allow for custom color transformations. http://docs.opencv.org/2.4/modules/imgproc/doc/miscellaneous_transformations.html#cvtcolor
类似于以下内容，但我使用的是OpenCV for C ++，而不是Python。
Similar to the following, but I am using OpenCV for C++, not Python.Apply transformation matrix to pixels in OpenCV image
推荐答案
基本上，链接的答案使用重塑来转换你的 CV_32FC3 垫尺寸 mxn 到 CV_32F 垫尺寸（mn）x 3 。之后，矩阵的每一行都包含一个像素的颜色通道。然后你可以应用通常的矩阵乘法来获得一个新的垫子并且重塑它可以回到具有三个通道的原始形状。
Basically the linked answer uses reshape to convert your CV_32FC3 mat of size m x n to a CV_32F mat of size (mn) x 3. After that, each row of the matrix contains exactly color channels of one pixel. You can then apply usual matrix multiplication to obtain a new mat and reshape it back to the original shape with three channels.
注意：值得注意的是opencv的默认颜色空间是BGR，而不是RGB。
Note: It may be worth noticing that the default color space of opencv is BGR, not RGB.
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