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In this article Xiaobian for you to introduce in detail "OpenCV traversing images through Mat methods are", detailed content, clear steps, details handled properly, I hope that this "OpenCV traversing images through Mat methods have" article can help you solve doubts, the following follow the editor's ideas slowly in-depth, together to learn new knowledge bar.

In practical application, we often operate on the image not as a whole, but on all the points or special points in the image, so traversing the image is very important. how to traverse the image efficiently is a problem worth discussing.

Color Reduce

Or use the classic example of Reduce Color, that is, to quantify the pixel representation in the image. If a common RGB24 image has 256x256x256 colors, and the pixels of each channel are reduced by 8 times to 256ppm by Reduce Color, there are only 32x32x32 colors in the image. Assuming that the multiple of quantization reduction is N, then the code is implemented as a simple value/N*N. Usually we add Nash 2 to get the intermediate value of the adjacent multiple of N, and finally the image is quantized into (256max N) × (256max N) × (256max N) colors.

And carry on the statistics to the color histogram of the image after color reduction.

Method 1. Modify the image pixels directly. At (iQuery j)

The Mat class provides an at method for getting points on an image, which is a template function that can fetch points on any type of image.

Void colorReduce (Mat& image,int div) {for (int itemo witi)

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