读入 RGB 文件并输出三个分量的概率分布示意图和熵

基本思路
1.读入一个RGB文件，创建3个空txt文件
2.开辟3个数组，将RGB数据从RGB文件中读出，并分别保存到3个数组中
3.计算各颜色通道数据概率分布，并写入txt文件
4.计算熵并输出
代码如下

#include<stdio.h>
#include<iostream>
#include<math.h>
using namespace std;
#define A  65536
int main()
{
 //打开,创建文件
 FILE* image, * red, * green,*blue; 
 fopen_s(&image, "C:\\Users\\XMGO\\Desktop\\数据压缩\\down.rgb", "rb");
 fopen_s(&red, "C:\\Users\\XMGO\\Desktop\\数据压缩\\Red.txt", "w");
 fopen_s(&green, "C:\\Users\\XMGO\\Desktop\\数据压缩\\Green.txt", "w");
 fopen_s(&blue, "C:\\Users\\XMGO\\Desktop\\数据压缩\\Blue.txt", "w");
 //定义R、G、B分量
 unsigned char R[A] = { 0 },G[A] = { 0 }, B[A] = { 0 };
 //定义频率分量
 double R_F[256] = { 0 },G_F[256] = { 0 },B_F[256] = { 0 };
 //定义熵
 double R_S = 0,G_S = 0, B_S = 0;
 //分别读取R、G、B三个分量到数组中
 unsigned char sum[256*256*3];
 fread(sum, 1, 256*256*3, image);
 for (int i = 0, j = 0; i < 256*256*3; i = i + 3, j++)
 {
  B[j] = *(sum + i);
  G[j] = *(sum + i + 1);
  R[j] = *(sum + i + 2); 
 }
 //计数三通道各颜色值次数
 for (int i = 0; i < 256; i++)
 {
  for (int j = 0; j < A; j++)
  {
   if (int(R[j] == i)) {R_F[i]++;}
   if (int(G[j] == i)) {G_F[i]++;}
   if (int(B[j] == i)) {B_F[i]++;}
  }
 }
//计算频率
 for (int i = 0; i < 256; i++)
 {
  R_F[i] = R_F[i] / (256 * 256);
  B_F[i] = B_F[i] / (256 * 256);
  G_F[i] = G_F[i] / (256 * 256);
 }
 //将频率写入文件
 fprintf(red, "值\t概率\n");
 for (int i = 0; i < 256; i++)
 {
  fprintf(red, "%d\t%f\n", i, R_F[i]);
 }
 fprintf(green, "值\t概率\n");
 for (int i = 0; i < 256; i++)
 {
  fprintf(green, "%d\t%f\n", i, G_F[i]);
 }
 fprintf(blue, "值\t概率\n");
 for (int i = 0; i < 256; i++)
 {
  fprintf(blue, "%d\t%f\n", i, B_F[i]);
 }
 //计算并输出熵
 for (int i = 0; i < 256; i++)
 {
  if (R_F[i] != 0) {R_S += -R_F[i] * log(R_F[i]) / log(2);}
  if (G_F[i] != 0) {G_S += -G_F[i] * log(G_F[i]) / log(2);}
  if (B_F[i] != 0) {B_S += -B_F[i] * log(B_F[i]) / log(2);}
 }
 cout << "R熵为" << R_S << endl;
 cout << "G熵为" << G_S << endl;
 cout << "B熵为" << B_S << endl;
 fclose(image);
 fclose(red);
 fclose(green);
 fclose(blue);
 return 0;
}
 

用matlab画图
red

green

blue