OpenCV4入门教程164:超分辨率

索引地址:系列索引

超分辨率(Super Resolution)指的是分辨率较高的比如4K、8K等等,但是一般这个做动词,指将低分辨率的视频图片通过某种方法变为高分辨率的行为,考虑到原始数据的状况,一般就是720P/1080P这样。

泰坦尼克号、终结者2这样的电影有过高清修复重映,一般就是将分辨率放大提高画质。这些都是胶片拍摄的。像一些电影、动漫等等,我们不是制作方没有原始数据,那么就只能通过软件的方式提升画质。

下面介绍OpenCV提供的超分辨率方法,实际在使用时一般使用神经网络+深度学习方法。比如

  • waifu2x
  • SRMD
  • Anime4k
  • Realsr

一些工具比如SFVI等工具就是整合上面的一些工具。

测试

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#include <iostream>
#include <iomanip>
#include <string>

#include "opencv2/core.hpp"
#include "opencv2/core/utility.hpp"
#include "opencv2/highgui.hpp"
#include "opencv2/imgproc.hpp"
#include "opencv2/superres.hpp"
#include "opencv2/superres/optical_flow.hpp"
#include "opencv2/opencv_modules.hpp"

using namespace std;
using namespace cv;
using namespace cv::superres;

static Ptr<DenseOpticalFlowExt> createOptFlow(string name);

int main(int argc, char *argv[])
{
// 1-Initialize the initial parameters

// Input and output video
string inputVideoName;
string outputVideoName;
if (argc > 1)
inputVideoName = argv[1];
else
inputVideoName = ".\\tree.avi";

if (argc > 2)
outputVideoName = argv[2];
else
outputVideoName = ".\\tree_superresolution.avi";

// Scale factor
const int scale = 4;

// Iterations count
const int iterations = 180;

// Radius of the temporal search area
const int temporalAreaRadius =4;

// Optical flow algorithm
string optFlow = "farneback";
// optFlow = "farneback";
// optFlow = "tvl1";
// optFlow = "brox";
// optFlow = "pyrlk";

// Playback speed ouput
double outputFps = 25.0;

// 2- Create an optical flow method
Ptr<DenseOpticalFlowExt> optical_flow = createOptFlow(optFlow);

if (optical_flow.empty())
return -1;

// 3- Create the superresolution method and set its parameters
Ptr<SuperResolution> superRes;
superRes = createSuperResolution_BTVL1();

superRes->setOpticalFlow(optical_flow);
superRes->setScale(scale);
superRes->setIterations(iterations);
superRes->setTemporalAreaRadius(temporalAreaRadius);

Ptr<FrameSource> frameSource;
frameSource = createFrameSource_Video(inputVideoName);

superRes->setInput(frameSource);

// Not use the first frame
Mat frame;
frameSource->nextFrame(frame);

// 4- Processing the input video with the superresolution
// Show the initial options
cout << "Input : " << inputVideoName << " " << frame.size() << endl;
cout << "Output : " << outputVideoName << endl;
cout << "Playback speed output : " << outputFps << endl;
cout << "Scale factor : " << scale << endl;
cout << "Iterations : " << iterations << endl;
cout << "Temporal radius : " << temporalAreaRadius << endl;
cout << "Optical Flow : " << optFlow << endl;
cout << endl;

VideoWriter writer;
double start_time,finish_time;

for (int i = 0;; ++i)
{
cout << '[' << setw(3) << i << "] : ";
Mat result;

// Calculate the processing time
start_time = getTickCount();
superRes->nextFrame(result);
finish_time = getTickCount();
cout << (finish_time - start_time)/getTickFrequency() << " secs, Size: " << result.size() << endl;

if (result.empty())
break;

// Show the result
imshow("Super Resolution", result);

if (waitKey(1000) > 0)
break;

// Save the result on output file
if (!outputVideoName.empty())
{
if (!writer.isOpened())
writer.open(outputVideoName, VideoWriter::fourcc('X', 'V', 'I', 'D'), outputFps, result.size());
writer << result;
}
}
writer.release();

return 0;
}

static Ptr<DenseOpticalFlowExt> createOptFlow(string name)
{
if (name == "farneback")
return createOptFlow_Farneback();

else if (name == "tvl1")
return createOptFlow_DualTVL1();

else if (name == "brox")
return createOptFlow_Brox_CUDA();

else if (name == "pyrlk")
return createOptFlow_PyrLK_CUDA();

else
cerr << "Incorrect Optical Flow algorithm - " << name << endl;

return Ptr<DenseOpticalFlowExt>();
}

用来测试的视频信息为

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$ ffprobe test.avi                          
...
Input #0, avi, from 'test.avi':
Duration: 00:00:16.53, start: 0.000000, bitrate: 1292 kb/s
Stream #0:0: Video: msmpeg4v2 (MP42 / 0x3234504D), yuv420p, 640x360, 1288 kb/s, 30 fps, 30 tbr, 30 tbn

原始视频为360p,30帧,时长为16秒

使用farneback模式进行放大,测试环境为戴尔G15 1511 i7-11800H 8核16线程,16G内存

测试程序输出为

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$ ./sr test.avi tsr.avi  
Input : test.avi [640 x 360]
Output : tsr.avi
Playback speed output : 25
Scale factor : 4
Iterations : 180
Temporal radius : 4
Optical Flow : farneback

[ 0] : 543.328 secs, Size: [2546 x 1426]
[ 1] : 86.5821 secs, Size: [2546 x 1426]
[ 2] : 89.9619 secs, Size: [2546 x 1426]
[ 3] : 89.7291 secs, Size: [2546 x 1426]
[ 4] : 89.9414 secs, Size: [2546 x 1426]
[ 5] : 90.3375 secs, Size: [2546 x 1426]
[ 6] : 91.1083 secs, Size: [2546 x 1426]
[ 7] : 91.6142 secs, Size: [2546 x 1426]
[ 8] : 91.4761 secs, Size: [2546 x 1426]
[ 9] : 91.6939 secs, Size: [2546 x 1426]
[ 10] : 91.86 secs, Size: [2546 x 1426]
[ 11] : 91.8984 secs, Size: [2546 x 1426]
[ 12] : 91.7052 secs, Size: [2546 x 1426]
[ 13] : 91.7788 secs, Size: [2546 x 1426]
[ 14] : 91.6301 secs, Size: [2546 x 1426]
[ 15] : 91.5122 secs, Size: [2546 x 1426]
[ 16] : 90.6578 secs, Size: [2546 x 1426]
[ 17] : 90.612 secs, Size: [2546 x 1426]
[ 18] : 91.185 secs, Size: [2546 x 1426]
...
[481] : 90.6462 secs, Size: [2546 x 1426]
[482] : 90.534 secs, Size: [2546 x 1426]
[483] : 90.8866 secs, Size: [2546 x 1426]
[484] : 90.6648 secs, Size: [2546 x 1426]
[485] : 96.7889 secs, Size: [2546 x 1426]
[486] : 89.6735 secs, Size: [2546 x 1426]
[487] : 77.6115 secs, Size: [2546 x 1426]
[488] : 68.7781 secs, Size: [2546 x 1426]
[489] : 61.9018 secs, Size: [2546 x 1426]
[490] : 0.00274725 secs, Size: [2546 x 1426]
[491] : 0.00269216 secs, Size: [2546 x 1426]
[492] : 0.00278245 secs, Size: [2546 x 1426]
[493] : 0.00277431 secs, Size: [2546 x 1426]
[494] : 0.00338189 secs, Size: [2546 x 1426]
[495] : 2.182e-06 secs, Size: [0 x 0]

从2022.04.29 20:19:22到2022.04.30 09:06:01耗时8个小时,期间CPU16核全满,内存接近全满,GPU未使用。

而且画质不太好,频繁出现花屏

result

输出的结果视频信息为:

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$ ffprobe tsr.avi 
...
Input #0, avi, from 'tsr.avi':
Metadata:
software : Lavf58.76.100
Duration: 00:00:19.80, start: 0.000000, bitrate: 19202 kb/s
Stream #0:0: Video: mpeg4 (Simple Profile) (XVID / 0x44495658), yuv420p, 2546x1426 [SAR 1:1 DAR 1273:713], 19230 kb/s, 25 fps, 25 tbr, 25 tbn

结果为1426p,25帧,时长19秒

总结

还是更现代化的好使一点


OpenCV4入门教程164:超分辨率
https://blog.jackeylea.com/opencv/opencv-super-resolution/
作者
JackeyLea
发布于
2020年11月10日
许可协议