CLAHE算法的C语言实现代码

以下是CLAHE算法的C语言实现代码：

#include <stdio.h>
#include <stdlib.h>
#include <math.h>

#define MAX_GREY 256

void histogram(int** image, int rows, int cols, int* hist, int max_grey);
void cum_histogram(int* hist, int max_grey);
void clip_histogram(int* hist, int max_grey, int clip_limit);
void map_histogram(int* hist, int max_grey, int num_pixels);
void equalize(int** image, int rows, int cols, int max_grey, int clip_limit);

int main() {
    // Read image data
    int rows, cols, max_grey;
    scanf("%d %d %d", &cols, &rows, &max_grey);
    int** image = (int**) malloc(rows * sizeof(int*));
    for (int i = 0; i < rows; i++) {
        image[i] = (int*) malloc(cols * sizeof(int));
        for (int j = 0; j < cols; j++) {
            scanf("%d", &image[i][j]);
        }
    }
    // Apply CLAHE algorithm
    int clip_limit = 4;
    equalize(image, rows, cols, max_grey, clip_limit);
    // Print equalized image data
    printf("%d %d %d\n", cols, rows, max_grey);
    for (int i = 0; i < rows; i++) {
        for (int j = 0; j < cols; j++) {
            printf("%d ", image[i][j]);
        }
        printf("\n");
    }
    return 0;
}

void histogram(int** image, int rows, int cols, int* hist, int max_grey) {
    for (int i = 0; i < max_grey; i++) {
        hist[i] = 0;
    }
    for (int i = 0; i < rows; i++) {
        for (int j = 0; j < cols; j++) {
            hist[image[i][j]]++;
        }
    }
}

void cum_histogram(int* hist, int max_grey) {
    for (int i = 1; i < max_grey; i++) {
        hist[i] += hist[i - 1];
    }
}

void clip_histogram(int* hist, int max_grey, int clip_limit) {
    int num_pixels = 0;
    for (int i = 0; i < max_grey; i++) {
        if (hist[i] > clip_limit) {
            hist[i] = clip_limit;
        }
        num_pixels += hist[i];
    }
    int excess = num_pixels - max_grey;
    for (int i = max_grey - 1; i >= 0 && excess > 0; i--) {
        if (hist[i] > clip_limit) {
            int reduction = fmin(excess, hist[i] - clip_limit);
            hist[i] -= reduction;
            excess -= reduction;
        }
    }
}

void map_histogram(int* hist, int max_grey, int num_pixels) {
    for (int i = 0; i < max_grey; i++) {
        hist[i] = round((max_grey - 1) * hist[i] / (float)num_pixels);
    }
}

void equalize(int** image, int rows, int cols, int max_grey, int clip_limit) {
    int* hist = (int*) malloc(max_grey * sizeof(int));
    int* cum_hist = (int*) malloc(max_grey * sizeof(int));
    histogram(image, rows, cols, hist, max_grey);
    cum_histogram(hist, max_grey);
    clip_histogram(hist, max_grey, clip_limit);
    map_histogram(hist, max_grey, rows * cols);
    for (int i = 0; i < rows; i++) {
        for (int j = 0; j < cols; j++) {
            image[i][j] = hist[image[i][j]];
        }
    }
    free(hist);
    free(cum_hist);
}

请注意，此代码仅适用于8位灰度图像。如果要处理其他类型的图像，需要进行适当的修改。此外，此代码还需要进行错误检查和内存管理。