视频质量评价工具实验文档
实验工具采用全参考的两个工具：
- MSU VQMT
- NetFlix vmaf
因为普遍使用psnr来做视频质量评价指标，本实验主要进行测试及对比，故只使用psnr作为两个工具的指标
区别：
-
VQMT是一个商业软件，现在的免费版能够支持HD, FullHD, 4k, 8k分辨率及Support for 200+ video & image formats
下载链接：MSU Video Quality Measurement Tool (VMAF, PSNR, VQM, SSIM, NIQE, etc) (compression.ru)
- Free 和 Pro的主要区别如下：（pro版价格昂贵，1 device 999$，可以选择ProDemo，同样是免费的版本，但是它官方表示不保证数据正确）
Features & Components Free ProDemo Pro PREMIUM GPU metrics − + + + HDR − + + + Windows Console − + + + Linux Console − + + + MAC (iOS) support − Planned Planned Planned Python Interface − + + + Unlimited installations + + − + Automatical activation N/A N/A − + Free updates + + 1 year 1 year Correct results (not DEMO) + − + + Usage in companies − + + + -
vmaf 只支持yuv、y4m格式，也提供了几种参数可供选择 （psnr, psnr_hvs, ssim, ms-ssim, ciede）
操作方法：
-
VQMT有图形界面可以直接打开视频文件进行比较
其同样具备多种参数可以使用，可选参数如下：（可以看到这里有Netflix VMAF）
输入原视频及参考视频URL或者打开文件后便可以开始进行分析，在新版本中还会自动保存分析的结果，只是不能进行批处理，需要Pro版本的命令行才能支持批处理工作。
-
vmaf没有图形界面，需要使用命令行工具来进行操作
命令行使用指南 vmaf/README.md at master · Netflix/vmaf (github.com)
-
指令：
vmaf -r E:\common\tang3.yuv -d E:\common\tang4.yuv -w 960 -h 960 -p 420 -b 8 -o output.log -
相关参数：
Reference .y4m or .yuv (-r/--reference) is required Usage: vmaf [options] Supported options: --reference/-r $path: path to reference .y4m or .yuv --distorted/-d $path: path to distorted .y4m or .yuv --width/-w $unsigned: width --height/-h $unsigned: height --pixel_format/-p: $string pixel format (420/422/444) --bitdepth/-b $unsigned: bitdepth (8/10/12/16) --model/-m $params: model parameters, colon ":" delimited `path=` path to model file `version=` built-in model version `name=` name used in log (optional) --output/-o $path: output file --xml: write output file as XML (default) --json: write output file as JSON --csv: write output file as CSV --sub: write output file as subtitle --threads $unsigned: number of threads to use --feature $string: additional feature Additional Metrics 其他的可选参数 psnr, psnr_hvs, ssim, ms-ssim, ciede A number of addtional metrics are supported. Enable these metrics with the --feature flag. # psnr, psnr_hvs, ssim, ms-ssim, ciede --feature psnr \ --feature psnr_hvs \ --feature float_ssim \ --feature float_ms_ssim --feature ciede --feature cambi --cpumask: $bitmask restrict permitted CPU instruction sets --frame_cnt $unsigned: maximum number of frames to process --subsample: $unsigned compute scores only every N frames --quiet/-q: disable FPS meter when run in a TTY --no_prediction/-n: no prediction, extract features only --version/-v: print version and exit
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输出：
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VQMT
- Y psnr (信噪比 Peak signal-to-noise ratio)；
将图片转化为 YCbCr 格式，然后只计算 Y 分量也就是亮度分量的 PSNR，图像压缩中典型的峰值信噪比值在 30 到 40dB 之间，越高越好。
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输出报表：
Metric: PSNR Color component: Y Files: constrait20fps.mp4 compared to: native_video.mp4 # native_video.mp4 0 48.089218 1 48.097214 2 40.957611 3 48.148323 4 47.362122 ...... ...... 10837 18.317478 10838 18.341671 10839 18.339325 10840 18.337685 10841 18.108231 10842 18.247126 10843 18.247503 10844 18.245304 total psnr 34.472847 mean 47.133518 harmonic mean 46.136684 min. val 16.455748 max. val 61.386471 min. frame 3623 max. frame 389 std dev 4.385028 variance 19.228470
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vmaf
- 未添加任何feature：
<VMAF version="2.3.1"> <params qualityWidth="960" qualityHeight="960" /> <fyi fps="20.94" /> <frames> <frame frameNum="0" integer_adm2="0.978963" integer_adm_scale0="0.998125" integer_adm_scale1="0.995882" integer_adm_scale2="0.990478" integer_adm_scale3="0.956561" integer_motion2="0.000000" integer_motion="0.000000" integer_vif_scale0="0.549783" integer_vif_scale1="0.619952" integer_vif_scale2="0.648450" integer_vif_scale3="0.675513" vmaf="59.246770" /> <frame frameNum="1" integer_adm2="0.991671" integer_adm_scale0="0.998279" integer_adm_scale1="0.994878" integer_adm_scale2="0.994040" integer_adm_scale3="0.986643" integer_motion2="0.852844" integer_motion="6.023301" integer_vif_scale0="0.815954" integer_vif_scale1="0.879384" integer_vif_scale2="0.898762" integer_vif_scale3="0.913492" vmaf="85.293165" /> ...... ...... </frames> <pooled_metrics> <metric name="integer_adm2" min="0.413357" max="0.999776" mean="0.928834" harmonic_mean="0.923530" /> <metric name="integer_adm_scale0" min="0.720963" max="1.001498" mean="0.978396" harmonic_mean="0.977443" /> <metric name="integer_adm_scale1" min="0.340115" max="1.003616" mean="0.940059" harmonic_mean="0.933984" /> <metric name="integer_adm_scale2" min="0.277522" max="0.999417" mean="0.926124" harmonic_mean="0.916255" /> <metric name="integer_adm_scale3" min="0.325116" max="0.999697" mean="0.911883" harmonic_mean="0.906875" /> <metric name="integer_motion2" min="0.000000" max="35.799564" mean="6.326431" harmonic_mean="3.413652" /> <metric name="integer_motion" min="0.000000" max="67.485893" mean="7.641753" harmonic_mean="3.884414" /> <metric name="integer_vif_scale0" min="0.096378" max="0.978172" mean="0.592144" harmonic_mean="0.571733" /> <metric name="integer_vif_scale1" min="0.105987" max="0.990578" mean="0.660542" harmonic_mean="0.639917" /> <metric name="integer_vif_scale2" min="0.104521" max="0.992963" mean="0.687723" harmonic_mean="0.666811" /> <metric name="integer_vif_scale3" min="0.098240" max="0.995127" mean="0.710630" harmonic_mean="0.689127" /> <metric name="vmaf" min="0.000000" max="96.823158" mean="63.415244" harmonic_mean="38.980743" /> </pooled_metrics> <aggregate_metrics /> </VMAF>- 添加psnr:
<VMAF version="e1d466c"> <params qualityWidth="576" qualityHeight="324" /> <fyi fps="41.98" /> <frames> <frame frameNum="0" integer_adm2="0.962084" integer_adm_scale0="0.946338" integer_adm_scale1="0.939006" integer_adm_scale2="0.957474" integer_adm_scale3="0.980887" integer_motion2="0.000000" integer_motion="0.000000" integer_vif_scale0="0.505712" integer_vif_scale1="0.879061" integer_vif_scale2="0.937873" integer_vif_scale3="0.964301" psnr_y="34.760779" psnr_cb="39.229987" psnr_cr="41.349703" vmaf="83.856285" /> ... </frames> <pooled_metrics> <metric name="integer_adm2" min="0.921008" max="0.962084" mean="0.934506" harmonic_mean="0.934463" /> ... <metric name="psnr_y" min="29.640688" max="34.760779" mean="30.755064" harmonic_mean="30.727905" /> <metric name="psnr_cb" min="38.019979" max="39.229987" mean="38.449441" harmonic_mean="38.447866" /> <metric name="psnr_cr" min="40.649266" max="41.353846" mean="40.991910" harmonic_mean="40.991083" /> <metric name="vmaf" min="71.176557" max="87.181420" mean="76.668905" harmonic_mean="76.510006" /> </pooled_metrics> <aggregate_metrics />
结论：
在使用上VQMT相对于vmaf因为具备图形界面的原因更加简单，在功能上VQMT带给我两点惊喜，第一点它能够使用vmaf metric，相当于可以覆盖vmaf的功能，另一点是计划在之后的版本中提供了流支持及更多参数，但是不知道能否在free 版本中使用。
Stream support
Allows VQMT read and estimate the quality of streamed video
对于有原视频和参考视频的视频评价，经过测试免费版本能够覆盖需求，并且新的免费版本14.1的VQMT同样能够支持高分辨率及多种像素格式。
综合评价下看，vmaf可以使用命令行进行批处理操作，这是它的一个优势，但是VQMT的简单易用及功能强大，并且对于目前的使用需求来看，不需要进行批处理操作，所以相对而言VQMT是目前进行全参考视频质量评价的最佳选择。