使用C语言编写一段对128×160数组实现中值滤波、直方图均衡以及行列投影的代码

以下是对128×160数组实现中值滤波、直方图均衡以及行列投影的C语言代码示例：

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

#define ROWS 128
#define COLS 160

// 中值滤波
void median_filter(unsigned char *src, unsigned char *dst) {
    int i, j, k, l;
    int window_size = 3;  // 窗口大小
    int median_index = (window_size * window_size) / 2;
    unsigned char window[window_size * window_size];
    
    for (i = 0; i < ROWS; i++) {
        for (j = 0; j < COLS; j++) {
            // 获取窗口内的像素值
            int index = 0;
            for (k = i - window_size/2; k <= i + window_size/2; k++) {
                for (l = j - window_size/2; l <= j + window_size/2; l++) {
                    if (k >= 0 && k < ROWS && l >= 0 && l < COLS) {
                        window[index++] = *(src + k*COLS + l);
                    }
                }
            }
            // 对窗口内的像素值排序
            for (k = 0; k < index - 1; k++) {
                for (l = k + 1; l < index; l++) {
                    if (window[k] > window[l]) {
                        unsigned char temp = window[k];
                        window[k] = window[l];
                        window[l] = temp;
                    }
                }
            }
            // 获取中值
            *(dst + i*COLS + j) = window[median_index];
        }
    }
}

// 直方图均衡
void histogram_equalization(unsigned char *src, unsigned char *dst) {
    int i, j;
    int hist[256] = {0};
    int cdf[256] = {0};
    int min = 255;
    
    // 获取像素值的直方图
    for (i = 0; i < ROWS; i++) {
        for (j = 0; j < COLS; j++) {
            hist[*(src + i*COLS + j)]++;
            if (*(src + i*COLS + j) < min) {
                min = *(src + i*COLS + j);
            }
        }
    }
    // 获取像素值的累计分布函数
    cdf[0] = hist[0];
    for (i = 1; i < 256; i++) {
        cdf[i] = cdf[i-1] + hist[i];
    }
    // 对累计分布函数进行归一化
    for (i = 0; i < 256; i++) {
        cdf[i] = ((cdf[i] - cdf[min]) * 255) / (ROWS * COLS - cdf[min]);
    }
    // 进行直方图均衡
    for (i = 0; i < ROWS; i++) {
        for (j = 0; j < COLS; j++) {
            *(dst + i*COLS + j) = cdf[*(src + i*COLS + j)];
        }
    }
}

// 行列投影
void row_col_projection(unsigned char *src, int *row_proj, int *col_proj) {
    int i, j;
    
    // 行投影
    for (i = 0; i < ROWS; i++) {
        int sum = 0;
        for (j = 0; j < COLS; j++) {
            sum += *(src + i*COLS + j);
        }
        *(row_proj + i) = sum / COLS;
    }
    // 列投影
    for (j = 0; j < COLS; j++) {
        int sum = 0;
        for (i = 0; i < ROWS; i++) {
            sum += *(src + i*COLS + j);
        }
        *(col_proj + j) = sum / ROWS;
    }
}

int main() {
    unsigned char *image = (unsigned char*)malloc(sizeof(unsigned char) * ROWS * COLS);
    unsigned char *filtered_image = (unsigned char*)malloc(sizeof(unsigned char) * ROWS * COLS);
    unsigned char *equalized_image = (unsigned char*)malloc(sizeof(unsigned char) * ROWS * COLS);
    int *row_proj = (int*)malloc(sizeof(int) * ROWS);
    int *col_proj = (int*)malloc(sizeof(int) * COLS);
    int i, j;
    
    // 初始化图像
    for (i = 0; i < ROWS; i++) {
        for (j = 0; j < COLS; j++) {
            *(image + i*COLS + j) = rand() % 256;
        }
    }
    
    // 中值滤波
    median_filter(image, filtered_image);
    
    // 直方图均衡
    histogram_equalization(image, equalized_image);
    
    // 行列投影
    row_col_projection(image, row_proj, col_proj);
    
    // 释放内存
    free(image);
    free(filtered_image);
    free(equalized_image);
    free(row_proj);
    free(col_proj);
    
    return 0;
}

以上代码中，我们定义了128×160的图像数组，实现了中值滤波、直方图均衡以及行列投影三种功能。其中，中值滤波使用了3×3的窗口，直方图均衡使用了基础的直方图均衡算法，行列投影分别计算了每一行和每一列的像素值平均数。