自适应直方图均衡化c++

以下是自适应直方图均衡化的C代码示例：

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

#define MAX_PIXELS 1000000

void adaptive_histogram_equalization(unsigned char *image, int rows, int cols, int window_size) {
    int i, j, k, n, m, index, sum, threshold;
    int offset = window_size / 2;
    int *histogram = (int*)calloc(256, sizeof(int));
    int *histogram_sum = (int*)calloc(256, sizeof(int));
    unsigned char *result = (unsigned char*)calloc(rows * cols, sizeof(unsigned char));
    if (histogram == NULL || histogram_sum == NULL || result == NULL) {
        printf("Memory allocation failed.\n");
        return;
    }
    for (i = 0; i < rows; i++) {
        for (j = 0; j < cols; j++) {
            for (k = 0; k < 256; k++) {
                histogram[k] = 0;
            }
            for (n = -offset; n <= offset; n++) {
                for (m = -offset; m <= offset; m++) {
                    if (i + n < 0 || i + n >= rows || j + m < 0 || j + m >= cols) {
                        continue;
                    }
                    index = (i + n) * cols + (j + m);
                    histogram[image[index]]++;
                }
            }
            histogram_sum[0] = histogram[0];
            for (k = 1; k < 256; k++) {
                histogram_sum[k] = histogram_sum[k - 1] + histogram[k];
            }
            sum = histogram_sum[255];
            threshold = (int)floor(sum / 2.0);
            for (k = 0; k < 256; k++) {
                if (histogram_sum[k] >= threshold) {
                    break;
                }
            }
            for (k = 0; k < 256; k++) {
                histogram[k] = (int)floor((double)histogram[k] * k / sum);
            }
            result[i * cols + j] = histogram[image[i * cols + j]];
        }
    }
    for (i = 0; i < rows; i++) {
        for (j = 0; j < cols; j++) {
            image[i * cols + j] = result[i * cols + j];
        }
    }
    free(histogram);
    free(histogram_sum);
    free(result);
}

int main(int argc, char *argv[]) {
    FILE *fp;
    unsigned char *image;
    int rows, cols, i, j;
    if (argc != 4) {
        printf("Usage: %s input_image output_image window_size\n", argv[0]);
        return 1;
    }
    fp = fopen(argv[1], "rb");
    if (fp == NULL) {
        printf("Failed to open input image.\n");
        return 1;
    }
    fseek(fp, 0, SEEK_END);
    long size = ftell(fp);
    fseek(fp, 0, SEEK_SET);
    if (size > MAX_PIXELS) {
        printf("Image size exceeds maximum limit.\n");
        fclose(fp);
        return 1;
    }
    image = (unsigned char*)calloc(size, sizeof(unsigned char));
    if (image == NULL) {
        printf("Memory allocation failed.\n");
        fclose(fp);
        return 1;
    }
    if (fread(image, sizeof(unsigned char), size, fp) != size) {
        printf("Failed to read input image.\n");
        fclose(fp);
        free(image);
        return 1;
    }
    fclose(fp);
    rows = sqrt(size);
    cols = rows;
    adaptive_histogram_equalization(image, rows, cols, atoi(argv[3]));
    fp = fopen(argv[2], "wb");
    if (fp == NULL) {
        printf("Failed to open output image.\n");
        free(image);
        return 1;
    }
    fwrite(image, sizeof(unsigned char), size, fp);
    fclose(fp);
    free(image);
    return 0;
}