在不适用opencv和imagemagick的基础上用C语言读入一张图像并对其进行中值滤波处理

如果不使用图像处理库，可以手动读取图像的像素值并对其进行中值滤波处理。以下是基于这种方法的C语言代码示例：

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

#define STBI_ONLY_PNG
#define STB_IMAGE_IMPLEMENTATION
#include "stb_image.h" //stb_image.h是一个轻量级的图像解码库

#define STB_IMAGE_WRITE_IMPLEMENTATION
#include "stb_image_write.h" //stb_image_write.h是一个轻量级的图像编码库

//计算一维中值
int median(int* arr, int size) {
    int i, j, temp;
    for (i = 0; i < size - 1; i++) {
        for (j = i + 1; j < size; j++) {
            if (arr[i] > arr[j]) {
                temp = arr[i];
                arr[i] = arr[j];
                arr[j] = temp;
            }
        }
    }
    if (size % 2 == 0) {
        return (arr[size / 2 - 1] + arr[size / 2]) / 2;
    }
    else {
        return arr[size / 2];
    }
}

int main(int argc, char** argv)
{
    if (argc != 3)
    {
        printf("Usage: %s <input_image_path> <output_image_path>\n", argv[0]);
        return -1;
    }

    int width, height, channels;
    unsigned char* image_data = stbi_load(argv[1], &width, &height, &channels, 0);

    if (!image_data)
    {
        printf("Could not open or find the image: %s\n", argv[1]);
        return -1;
    }

    unsigned char* image_data_filtered = (unsigned char*)malloc(width * height * channels * sizeof(unsigned char));

    int window_size = 5;
    int window_half_size = window_size / 2;

    for (int y = 0; y < height; y++) {
        for (int x = 0; x < width; x++) {
            for (int c = 0; c < channels; c++) {
                int values[25];
                int count = 0;
                for (int wy = -window_half_size; wy <= window_half_size; wy++) {
                    for (int wx = -window_half_size; wx <= window_half_size; wx++) {
                        int nx = x + wx;
                        int ny = y + wy;
                        if (nx >= 0 && nx < width && ny >= 0 && ny < height) {
                            values[count] = image_data[(ny * width + nx) * channels + c];
                            count++;
                        }
                    }
                }
                image_data_filtered[(y * width + x) * channels + c] = median(values, count);
            }
        }
    }

    stbi_write_png(argv[2], width, height, channels, image_data_filtered, width * channels);

    stbi_image_free(image_data);
    free(image_data_filtered);

    return 0;
}

此代码中使用了stb_image.h和stb_image_write.h两个轻量级的图像处理库，其中stb_image.h用于读取图像，stb_image_write.h用于保存图像。中值滤波处理的实现使用了一个$5 \times 5$的窗口，对于每个像素的每个通道，先将窗口内的像素值存入一个一维数组中，然后对该数组进行排序并取其中值作为该像素通道的新值。