[图像处理] YUV图像处理入门3
5 yuv420格式的灰阶测试图
本程序中的函数主要是为YUV420P视频数据流的第一帧图像添加边框。函数的代码如下所示：
/**
* @file 5 yuv_graybar.cpp
* @author luohen
* @brief gray scale bar of yuv
* @date 2018-12-07
*
*/
#include "stdafx.h"
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <math.h>
#include <iostream>
using namespace std;
/**
* @brief
*
* @param width width of input yuv420p file
* @param height height of input yuv420p file
* @param ymin minimum value of y
* @param ymax maximum value of y
* @param barnum Number of bars
* @param url location of input yuv420p file
* @return int
*/
int yuv420_graybar(int width, int height, int ymin, int ymax, int barnum, const char *url)
{
//每个灰度条的宽度
int barwidth;
//每个灰度阶次范围
float lum_inc;
//计算Y值
unsigned char lum_temp;
//uv分量宽高
int uv_width, uv_height;
//reading yuv image
FILE *input_fp;
if ((input_fp = fopen(url, "rb")) == NULL)
{
printf("%s open error!\n", url);
return -1;
}
else
{
printf("%s open.\n", url);
}
//writing yuv image
FILE *output_fp = fopen("video_result/gray_test.yuv", "wb+");
int t = 0, i = 0, j = 0;
//每个灰度条的宽度
barwidth = width / barnum;
//每个灰度阶次范围
lum_inc = ((float)(ymax - ymin)) / ((float)(barnum - 1));
//uv分量宽高
uv_width = width / 2;
uv_height = height / 2;
unsigned char *data_y = new unsigned char[width * height];
unsigned char *data_u = new unsigned char[uv_width * uv_height];
unsigned char *data_v = new unsigned char[uv_width * uv_height];
//Output Info
//输出信息
printf("Y, U, V value from picture's left to right:\n");
for (t = 0; t < (width / barwidth); t++)
{
//计算Y值
lum_temp = ymin + (char)(t * lum_inc);
printf("%3d, 128, 128\n", lum_temp);
}
//保存数据
for (j = 0; j < height; j++)
{
for (i = 0; i < width; i++)
{
t = i / barwidth;
lum_temp = ymin + (char)(t * lum_inc);
data_y[j * width + i] = lum_temp;
}
}
for (j = 0; j < uv_height; j++)
{
for (i = 0; i < uv_width; i++)
{
data_u[j * uv_width + i] = 128;
}
}
for (j = 0; j < uv_height; j++)
{
for (i = 0; i < uv_width; i++)
{
data_v[j * uv_width + i] = 128;
}
}
fwrite(data_y, width * height, sizeof(unsigned char), output_fp);
fwrite(data_u, uv_width * uv_height, sizeof(unsigned char), output_fp);
fwrite(data_v, uv_width * uv_height, sizeof(unsigned char), output_fp);
fclose(input_fp);
fclose(output_fp);
delete[] data_y;
delete[] data_u;
delete[] data_v;
return 0;
}
/**
* @brief main
*
* @return int
*/
int main()
{
int state = yuv420_graybar(640, 360, 0, 255, 10, "video/graybar.yuv");
return 0;
}调用函数为：
int yuv420_graybar(int width, int height, int ymin, int ymax, int barnum, const char *url);实际上这部分代码和前面代码差不多，先取得YUV数据流，类似一个一维数组，读第一帧图像，然后依次读到y，u，v三个分量起始位置，再对y，u，v的像素值分别进行处理。
结果如图所示：
6 两张yuv420p图像的峰值信噪比（psnr）计算
本程序中的函数主要是比较两张yuv420p图像的峰值信噪。函数的代码如下所示：
/**
* @file 6 yuv420_psnr.cpp
* @author luohen
* @brief Compute the PSNR values of two yuv files
* @date 2018-12-08
*
*/
#include "stdafx.h"
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <math.h>
#include <iostream>
using namespace std;
/**
* @brief
*
* @param url1 location of input yuv420p file1
* @param url2 location of input yuv420p file2
* @param w width of input yuv420p file
* @param h height of input yuv420p file
* @return int
*/
int yuv420_psnr(const char *url1, const char *url2, int w, int h)
{
//reading yuv iamges
FILE *fp1 = fopen(url1, "rb+");
FILE *fp2 = fopen(url2, "rb+");
unsigned char *pic1 = new unsigned char[w * h];
unsigned char *pic2 = new unsigned char[w * h];
fread(pic1, 1, w * h, fp1);
fread(pic2, 1, w * h, fp2);
double mse_sum = 0, mse = 0, psnr = 0;
//computing mse
for (int j = 0; j < w * h; j++)
{
mse_sum += pow((double)(pic1[j] - pic2[j]), 2);
}
mse = mse_sum / (w * h);
//computing psnr
psnr = 10 * log10(255.0 * 255.0 / mse);
printf("%5.3f\n", psnr);
delete[] pic1;
delete[] pic2;
fclose(fp1);
fclose(fp2);
return 0;
}
/**
* @brief main
*
* @return int
*/
int main()
{
int state = yuv420_psnr("video/akiyo.yuv", "video/distort_akiyo.yuv", 352, 288);
return 0;
}调用函数为：
int yuv420_psnr(const char *url1, const char *url2, int w, int h);这段代码主要是计算两张图像的接近程度，psnr值具体介绍可以见文章：
https://www.cnblogs.com/ranjiewen/p/6390846.html。
本文所用的两张图像一张是akiyo视频流首帧图像，另外一张是前面为akiyo加上边框的图像。两张图像的psnr值为13.497。一般psnr值越大两张图像越接近。
7 yuv420图像顺时针旋转90度
本程序中的函数主要是将YUV420P视频数据流的第一帧图像顺时针旋转90度。函数的代码如下所示：
/**
* @file 7 yuv_Rotation90.cpp
* @author luohen
* @brief 90 degree rotation of yuv420 images
* @date 2018-12-08
*
*/
#include "stdafx.h"
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <math.h>
#include <iostream>
using namespace std;
/**
* @brief Pre-defined image size
*
*/
#define image_h 288
#define image_w 352
/**
* @brief
*
* @param url location of input yuv420p file
* @return int
*/
int yuv420_Rotation90(const char *url)
{
//reading yuv files
FILE *input_fp;
//writingyuv files
FILE *output_fp = fopen("video_result/output_rotation.yuv", "wb+");
//reading yuv datas
if ((input_fp = fopen(url, "rb")) == NULL)
{
printf("%s open error!\n", url);
return -1;
}
else
{
printf("%s open.\n", url);
}
//Input image array definition
unsigned char input_Y[image_h][image_w];
unsigned char input_U[image_h / 2][image_w / 2];
unsigned char input_V[image_h / 2][image_w / 2];
//Output image array definition
unsigned char output_Y[image_w][image_h];
unsigned char output_U[image_w / 2][image_h / 2];
unsigned char output_V[image_w / 2][image_h / 2];
int w = image_w;
int h = image_h;
fread(input_Y, sizeof(unsigned char), w * h, input_fp);
fread(input_U, sizeof(unsigned char), w / 2 * h / 2, input_fp);
fread(input_V, sizeof(unsigned char), w / 2 * h / 2, input_fp);
//Y 90 degree rotation
for (int x = 0; x < h; x++)
{
for (int y = 0; y < w; y++)
{
//旋转之后，输出的x值等于输入的y坐标值
//y值等于输入列高-输入x坐标值-1
output_Y[y][h - x - 1] = input_Y[x][y];
}
}
//u 90 degree rotation
for (int x = 0; x < h / 2; x++)
{
for (int y = 0; y < w / 2; y++)
{
//旋转之后，输出的x值等于输入的y坐标值
//y值等于输入列高-输入x坐标值-1
output_U[y][h / 2 - x - 1] = input_U[x][y];
}
}
//v 90 degree rotation
for (int x = 0; x < h / 2; x++)
{
for (int y = 0; y < w / 2; y++)
{
//旋转之后，输出的x值等于输入的y坐标值
//y值等于输入列高-输入x坐标值-1
output_V[y][h / 2 - x - 1] = input_V[x][y];
}
}
fwrite(output_Y, sizeof(unsigned char), w * h, output_fp);
fwrite(output_U, sizeof(unsigned char), w / 2 * h / 2, output_fp);
fwrite(output_V, sizeof(unsigned char), w / 2 * h / 2, output_fp);
fclose(input_fp);
fclose(output_fp);
return 0;
}
/**
* @brief main
*
* @return int
*/
int main()
{
int state = yuv420_Rotation90("video/akiyo.yuv");
return 0;
}调用函数为：
int yuv420_Rotation90(const char *url);这段代码主要是分别提取yuv分量，然后将y，u，v分量分别旋转90度。但是提取yuv分量和以前的代码有所不同。
首先是建立yuv三个分量输入的静态二维数组，相比使用动态数组，这种方式处理数据简单很多，但是需要实现确定输入图像的大小。
unsigned char input_Y[image_h][image_w];
unsigned char input_U[image_h / 2][image_w / 2];
unsigned char input_V[image_h / 2][image_w / 2];然后建立旋转后的输出数组，输出数组定义是，由于是旋转90度，长宽进行了对调。
unsigned char output_Y[image_w][image_h];
unsigned char output_U[image_w / 2][image_h / 2];
unsigned char output_V[image_w / 2][image_h / 2];其他旋转操作，就是图像赋值过程。旋转后akiyo图像尺寸变为（288，352）
结果如图所示：
8 yuv420图像大小重置
本程序中的函数主要是对YUV420P视频数据流的第一帧图像进行缩放或者放大。类似opencv中的resize函数，函数的代码如下所示：
/**
* @file 8 yuv_resize.cpp
* @author luohen
* @brief adjusting yuv image size
* @date 2018-12-08
*
*/
#include "stdafx.h"
#include <stdio.h>
#include <stdlib.h>
#include <string.h>
#include <math.h>
#include <string.h>
#include <iostream>
using namespace std;
#define HEIGHT 288
#define WIDTH 352
/**
* @brief
*
* @param url location of input yuv420p file
* @param out_width output image width
* @param out_height output image height
* @return int
*/
int yuv420_resize(const char *url, int out_width, int out_height)
{
//input array
unsigned char yin[HEIGHT][WIDTH];
unsigned char uin[HEIGHT / 2][WIDTH / 2];
unsigned char vin[HEIGHT / 2][WIDTH / 2];
//output array
unsigned char *yout = new unsigned char[out_width * out_height];
unsigned char *uout = new unsigned char[out_width / 2 * out_height / 2];
unsigned char *vout = new unsigned char[out_width / 2 * out_height / 2];
///reading yuv file
FILE *input_fp;
//writing yuv file
FILE *output_fp = fopen("video_result/output_resize.yuv", "wb+");
if ((input_fp = fopen(url, "rb")) == NULL)
{
printf("%s open error!\n", url);
return -1;
}
else
{
printf("%s open.\n", url);
}
fread(yin, sizeof(unsigned char), HEIGHT * WIDTH, input_fp);
fread(uin, sizeof(unsigned char), HEIGHT * WIDTH / 4, input_fp);
fread(vin, sizeof(unsigned char), HEIGHT * WIDTH / 4, input_fp);
//Y
for (int i = 0; i < out_height; i++)
{
for (int j = 0; j < out_width; j++)
{
int i_in = round(i * HEIGHT / out_height);
int j_in = round(j * WIDTH / out_width);
yout[i * out_width + j] = yin[i_in][j_in];
}
}
//U
for (int i = 0; i < out_height / 2; i++)
{
for (int j = 0; j < out_width / 2; j++)
{
int i_in = round(i * (HEIGHT / 2) / (out_height / 2));
int j_in = round(j * (WIDTH / 2) / (out_width / 2));
uout[i * out_width / 2 + j] = uin[i_in][j_in];
}
}
//V
for (int i = 0; i < out_height / 2; i++)
{
for (int j = 0; j < out_width / 2; j++)
{
int i_in = round(i * (HEIGHT / 2) / (out_height / 2));
int j_in = round(j * (WIDTH / 2) / (out_width / 2));
vout[i * out_width / 2 + j] = vin[i_in][j_in];
}
}
fwrite(yout, sizeof(unsigned char), out_width * out_height, output_fp);
fwrite(uout, sizeof(unsigned char), out_width * out_height / 4, output_fp);
fwrite(vout, sizeof(unsigned char), out_width * out_height / 4, output_fp);
delete[] yout;
delete[] uout;
delete[] vout;
fclose(input_fp);
fclose(output_fp);
return 0;
}
/**
* @brief main
*
* @return int
*/
int main()
{
int state = yuv420_resize("video/akiyo.yuv", 288, 352);
return 0;
}调用函数为：
int yuv420_resize(const char *url, int out_width, int out_height);这段代码也是通过事先设定yuv输入输出的静态二维数组来进行处理的。其中out_width, out_height
是输出图像的宽高，这段代码中输出图像的宽高可以设定为任意值。所用图像resize方法是最简单的最邻近插值法。
插值方法见文章：
https://blog.csdn.net/caomin1hao/article/details/81092134。
当设置调整后的图像宽高为288，352时，结果如下：
本文来自博客园，作者：落痕的寒假，转载请注明原文链接：https://www.cnblogs.com/luohenyueji/p/16970337.html
