图像处理入门系列文章

C语言生成RGB24格式图像纯C语言实现

图像缩放之最近邻内插法数学原理和纯C语言实现

图像直方图均衡化(Equalization)数学原理和纯C语言实现

图像直方图规定化(Specification)数学原理和纯C语言实现

图像处理入门系列文章

一、图像规定化数学原理

1.转化为数学问题

2.需要用到的知识

3.数学推理

二、程序实现

1.程序实现原理

2.代码实现

3.程序执行效果

4.图像规定化前后效果

总结

一、图像规定化数学原理

1.转化为数学问题

2.需要用到的知识

一维函数微积分
随机变量的概率分布

3.数学推理

二、程序实现

1.程序实现原理

2.代码实现

代码如下（示例）：

#include <stdlib.h>
#include <stdio.h>#define PICT_WIDTH  90
#define PICT_HEIGHT  60static unsigned int s_rgb[PICT_WIDTH][PICT_HEIGHT][3] = { 0 };/**
* rgb24
* r:203 g:64,173,38 b:142
*/
int make_rgb24_colorbar(unsigned int rgb[90][60][3])
{int i = 0;int j = 0;unsigned char chr = 0;for (j = 0; j<PICT_HEIGHT; j++){for (i = 0; i < PICT_WIDTH; i++){if (i<30) {chr = 203;}else if (i<60) {chr = 64;}else {chr = 0;}rgb[i][j][0] = chr;if (i<30){chr = 0;}else if (i<60){chr = 173;}else{chr = 0;}rgb[i][j][1] = chr;if (i<30){chr = 0;}else if (i<60){chr = 38;}else{chr = 142;}rgb[i][j][2] = chr;}}return 0;
}int generate_rgb24_file(unsigned int rgb[90][60][3],char *file_name)
{char file_path[64] = {0};if (file_name == NULL) {return 0;}snprintf(file_path,63,"rgb_%s_90_60.rgb24", file_name);FILE *fp = fopen(file_path, "wb+");int i = 0;int j = 0;unsigned char chr = 0;for (j = 0; j< PICT_HEIGHT; j++){for (i = 0; i < PICT_WIDTH; i++){chr = rgb[i][j][0];fwrite(&chr, 1, 1, fp);chr = rgb[i][j][1];fwrite(&chr, 1, 1, fp);chr = rgb[i][j][2];fwrite(&chr, 1, 1, fp);}}fclose(fp);return 0;
}#define IMAGE_COLOR_LEVEL 256#define HISTOGRAM_HEIGHT_MAX 20
#define HISTOGRAM_WIDTH_MAX 128#define STATISTIC_DEC_MAX 5
#define STATISTIC_HOR_AXS_NUM (HISTOGRAM_WIDTH_MAX / STATISTIC_DEC_MAX)int print_histogram(int image_statistic[IMAGE_COLOR_LEVEL],char *name)
{int *image_point = image_statistic;char hist_char = '*';char hist_space_char = ' ';char disp_array[HISTOGRAM_HEIGHT_MAX][HISTOGRAM_WIDTH_MAX + 1] = {0};int hist_statistic[HISTOGRAM_WIDTH_MAX] = {0};int i = 0;int j = 0;int k = 0;int statistic_max = 0;int hist_hor_axis[STATISTIC_HOR_AXS_NUM] = { 0 };for (i = 0; i < IMAGE_COLOR_LEVEL; i++){hist_statistic[i * HISTOGRAM_WIDTH_MAX / IMAGE_COLOR_LEVEL] += image_statistic[i];}for (i = 0; i < STATISTIC_HOR_AXS_NUM; i++){hist_hor_axis[i] = 1.0 * STATISTIC_DEC_MAX * i * IMAGE_COLOR_LEVEL / HISTOGRAM_WIDTH_MAX;}for (i = 0; i < HISTOGRAM_WIDTH_MAX; i++){if (hist_statistic[i] > statistic_max){statistic_max = hist_statistic[i];}}for (i = 0; i < HISTOGRAM_WIDTH_MAX;i++){int hist_height = statistic_max == 0 ? 0 : hist_statistic[i] * HISTOGRAM_HEIGHT_MAX / statistic_max;for (j = 0; j < HISTOGRAM_HEIGHT_MAX; j++){if (j < hist_height){disp_array[j][i] = hist_char;}else{disp_array[j][i] = hist_space_char;}}}printf("     y\n""      \n""     |\n""%5d|\n", statistic_max);for (i = 0; i < HISTOGRAM_HEIGHT_MAX; i++){printf("     |%s\n", disp_array[HISTOGRAM_HEIGHT_MAX - i - 1]);}printf("     |--------------------------------------------------------------------------------------------------------------------------------->x\n");printf("     ");char dec_max[32] = { 0 };char format_str[32] = "%-";sprintf(dec_max, "%d", STATISTIC_DEC_MAX);strncat(format_str, dec_max,32);strncat(format_str, "d", 32);for (i = 0; i < STATISTIC_HOR_AXS_NUM; i++){printf(format_str, hist_hor_axis[i]);}printf("\n");if(name != NULL){int name_size = strlen(name);if(name_size < HISTOGRAM_WIDTH_MAX){int space = (HISTOGRAM_WIDTH_MAX - name_size) / 2;for (i = 0; i < space; i++){printf(" ");}printf("%s\n\n",name);}}   return 0;
}int statistic_histogram(unsigned int rgb[90][60][3],int image_statistic[IMAGE_COLOR_LEVEL])
{int i = 0;int j = 0;int k = 0;for(i = 0; i < 90; i++){for (j = 0; j < 60; j++) {for (k = 0; k < 3; k++){image_statistic[rgb[i][j][k]]++;}}}return 0;
}//直方图规定化
int histogram_specification(unsigned int rgb[90][60][3], unsigned int result_rgb[90][60][3],int image_statistic_spec[IMAGE_COLOR_LEVEL])
{int image_statistic[IMAGE_COLOR_LEVEL] = {0};int i = 0;int j = 0;int k = 0;int tmp = 0;int pixel_num = 90 * 60 * 3;float ratio = 0;float equal_ratio[IMAGE_COLOR_LEVEL] = { 0 };int spec_acc = 0;int equal_map[IMAGE_COLOR_LEVEL] = {0};int spec_equal_map[IMAGE_COLOR_LEVEL] = {0};float equal_spec_ratio[IMAGE_COLOR_LEVEL] = { 0 };int spec_map[IMAGE_COLOR_LEVEL] = {0};statistic_histogram(rgb, image_statistic);for (i = 0; i < IMAGE_COLOR_LEVEL; i++){if(image_statistic[i] != 0){printf("before,i:[%d],num:[%d]\n",i,image_statistic[i]);}}//原分布求累计概率for (i = 0; i < IMAGE_COLOR_LEVEL; i++){for (j = 0; j < i + 1; j++) {equal_ratio[i] += image_statistic[j] * 1.0 / pixel_num;}}//均衡化映射表for (i = 0; i < IMAGE_COLOR_LEVEL; i++){equal_map[i] = (unsigned int)(IMAGE_COLOR_LEVEL - 1) * equal_ratio[i];//printf("equal i:[%d],des:[%d]\n",i,equal_map[i]);}//目标分布归一化for (i = 0; i < IMAGE_COLOR_LEVEL; i++){spec_acc += image_statistic_spec[i];}//原分布求累计概率for (i = 0; i < IMAGE_COLOR_LEVEL; i++){for (j = 0; j < i + 1; j++) {equal_spec_ratio[i] += image_statistic_spec[j] * 1.0 / spec_acc;}}//均衡化映射表for (i = 0; i < IMAGE_COLOR_LEVEL; i++){spec_equal_map[i] = (unsigned int)(IMAGE_COLOR_LEVEL - 1) * equal_spec_ratio[i];//printf("spec_equal i:[%d],des:[%d]\n",i,spec_equal_map[i]);}//映射匹配for (i = 0; i < IMAGE_COLOR_LEVEL; i++){int diff = IMAGE_COLOR_LEVEL;int index = 0;for (j = 0; j < IMAGE_COLOR_LEVEL; j++){tmp = equal_map[i] - spec_equal_map[j] > 0 ? equal_map[i] - spec_equal_map[j] : spec_equal_map[j] - equal_map[i];if(tmp < diff){diff = tmp;index  = j;}}spec_map[i] = index;}//生成最终图像for (i = 0; i < 90; i++){for (j = 0; j < 60; j++){for (k = 0; k < 3; k++){result_rgb[i][j][k] = (unsigned int)spec_map[rgb[i][j][k]];//printf("[%d][%d][%d][%d]\n",i,j,k,result_rgb[i][j][k]);}}}int image_statistic2[IMAGE_COLOR_LEVEL] = {0};statistic_histogram(result_rgb, image_statistic2);for (i = 0; i < IMAGE_COLOR_LEVEL; i++){if(image_statistic2[i] != 0){printf("after,i:[%d],num:[%d]\n",i,image_statistic2[i]);}}return 0;
}int main()
{int image_statistic[IMAGE_COLOR_LEVEL] = {0};make_rgb24_colorbar(s_rgb);generate_rgb24_file(s_rgb, "colorbar");statistic_histogram(s_rgb, image_statistic);printf("\n ");print_histogram(image_statistic,"source image histogram");unsigned int result_rgb[90][60][3];int result_statistic[IMAGE_COLOR_LEVEL] = { 0 };int image_statistic_spec[IMAGE_COLOR_LEVEL] = {8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,8,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,20,20,20,20,20,20,20,20,20,20,20,20,20,20,20,20,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,36,36,36,36,36,36,36,36,36,36,36,36,36,36,36,36,40,40,40,40,40,40,40,40,40,40,40,40,40,40,40,40,36,36,36,36,36,36,36,36,36,36,36,36,36,36,36,36,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,32,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,28,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,24,20,20,20,20,20,20,20,20,20,20,20,20,20,20,20,20,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,16,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,12,};print_histogram(image_statistic_spec,"expected image histogram");histogram_specification(s_rgb, result_rgb, image_statistic_spec);statistic_histogram(result_rgb, result_statistic);print_histogram(result_statistic,"destination image histogram");generate_rgb24_file(result_rgb,"specification");sleep(100);;return 0;
}

3.程序执行效果

4.图像规定化前后效果

规定化前：

规定化后：

总结

需要用实际图像测试。

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图像直方图规定化(Specification)数学原理和纯C语言实现

图像处理入门系列文章

一、图像规定化数学原理

1.转化为数学问题

2.需要用到的知识

3.数学推理

二、程序实现

1.程序实现原理

2.代码实现

3.程序执行效果

4.图像规定化前后效果

总结

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