C语言实现图像线状噪声去除的DTV正则化优化问题

#include <stdio.h>\n#include <stdlib.h>\n#include <math.h>\n\n// 定义图像的宽度和高度\n#define WIDTH 640\n#define HEIGHT 480\n\n// 定义DTV正则化优化问题函数\nvoid dtv_regularization(float lambda, float alpha, int iterations, float *image) {\n int i, j, k;\n int index;\n float *u = (float *)malloc(WIDTH * HEIGHT * sizeof(float));\n float *p = (float *)malloc(WIDTH * HEIGHT * sizeof(float));\n float *q = (float *)malloc(WIDTH * HEIGHT * sizeof(float));\n float *g = (float *)malloc(WIDTH * HEIGHT * sizeof(float));\n \n // 初始化u、p、q、g\n for (i = 0; i < WIDTH; i++) {\n for (j = 0; j < HEIGHT; j++) {\n index = j * WIDTH + i;\n u[index] = image[index];\n p[index] = 0.0;\n q[index] = 0.0;\n g[index] = 0.0;\n }\n }\n \n // 迭代计算\n for (k = 0; k < iterations; k++) {\n for (i = 1; i < WIDTH - 1; i++) {\n for (j = 1; j < HEIGHT - 1; j++) {\n index = j * WIDTH + i;\n \n // 计算p和q\n p[index] = (u[index + 1] - u[index]) / alpha;\n q[index] = (u[index + WIDTH] - u[index]) / alpha;\n \n // 计算g\n g[index] = 1.0 / sqrt(p[index] * p[index] + q[index] * q[index] + lambda);\n \n // 更新u\n u[index] = (u[index] + lambda * (p[index] * g[index] + q[index] * g[index] - g[index])) / (1.0 + lambda * g[index]);\n }\n }\n }\n \n // 输出结果\n for (i = 0; i < WIDTH; i++) {\n for (j = 0; j < HEIGHT; j++) {\n index = j * WIDTH + i;\n printf("%f ", u[index]);\n }\n printf("\n");\n }\n \n // 释放内存\n free(u);\n free(p);\n free(q);\n free(g);\n}\n\n// 主函数\nint main() {\n // 定义测试图像\n float image[WIDTH * HEIGHT];\n \n // 初始化测试图像\n for (int i = 0; i < WIDTH; i++) {\n for (int j = 0; j < HEIGHT; j++) {\n int index = j * WIDTH + i;\n image[index] = rand() % 256; // 随机生成0-255之间的像素值\n }\n }\n \n // 调用DTV正则化优化问题函数\n dtv_regularization(0.1, 0.2, 100, image);\n \n return 0;\n}