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：

添加图片注释，不超过 140 字（可选）

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：

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：

添加图片注释，不超过 140 字（可选）

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：

当设置调整后的图像宽高为288，352时，结果如下：

添加图片注释，不超过 140 字（可选）

引用链接

[1] :

[2] :