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https://github.com/rolinh/VQMT

VQMT: Video Quality Measurement Tool. Fast implementations of the following objective image quality metrics: PSNR, SSIM, MS-SSIM, VIFp, PSNR-HVS and PSNR-HVS-M.
https://github.com/rolinh/VQMT

metrics ms-ssim psnr psnr-hvs psnr-hvs-m ssim video vifp yuv

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VQMT: Video Quality Measurement Tool. Fast implementations of the following objective image quality metrics: PSNR, SSIM, MS-SSIM, VIFp, PSNR-HVS and PSNR-HVS-M.

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README 

        
# VQMT - Video Quality Measurement Tool



This software provides fast implementations of the following objective metrics:



* **PSNR**: Peak Signal-to-Noise Ratio,

* **SSIM**: Structural Similarity,

* **MS-SSIM**: Multi-Scale Structural Similarity,

* **VIFp**: Visual Information Fidelity, pixel domain version

* **PSNR-HVS**: Peak Signal-to-Noise Ratio taking into account Contrast

  Sensitivity Function (CSF),

* **PSNR-HVS-M**: Peak Signal-to-Noise Ratio taking into account Contrast

  Sensitivity Function (CSF) and between-coefficient contrast masking of DCT

  basis functions.



In this software, the above metrics are implemented in C++ with the help of

OpenCV and are based on the original Matlab implementations provided by their

developers.

The source code of this software can be compiled on any platform and

only requires the OpenCV library (core and imgproc modules).

This software allows performing video quality assessment without using Matlab

and shows better performance than Matlab in terms of run time.



# PREREQUISITE



The OpenCV library (http://opencv.willowgarage.com/wiki/) needs to be installed

to be able to compile this code. Only the core and imgproc modules are required.



# BUILD



CMake is required in order to build VQMT. A Makefile is provided to ease the

building step:



	make



This command has the effect of creating the `build` directory, calling

`cmake` within it and building VQMT. The binary may then be found in

`build/bin/Release`.



# USAGE



```

vqmt (or VQMT.exe on Windows) OriginalVideo ProcessedVideo Height Width NumberOfFrames ChromaFormat Output Metrics

```



- **OriginalVideo**: the original video as raw YUV video file, progressively

  scanned, and 8 bits per sample

- **ProcessedVideo**: the processed video as raw YUV video file, progressively

  scanned, and 8 bits per sample

- **Height**: the height of the video

- **Width**: the width of the video

- **NumberOfFrames**: the number of frames to process

- **ChromaFormat**: the chroma subsampling format. 0: YUV400, 1: YUV420,

  2: YUV422, 3: YUV444

- **Output**: the name of the output file(s)

- **Metrics**: the list of metrics to use



Available metrics:

- **PSNR**: Peak Signal-to-Noise Ratio (PNSR)

- **SSIM**: Structural Similarity (SSIM)

- **MSSSIM**: Multi-Scale Structural Similarity (MS-SSIM)

- **VIFP**: Visual Information Fidelity, pixel domain version (VIFp)

- **PSNRHVS**: Peak Signal-to-Noise Ratio taking into account Contrast

  Sensitivity Function (CSF) (PSNR-HVS)

- **PSNRHVSM**: Peak Signal-to-Noise Ratio taking into account Contrast

  Sensitivity Function (CSF) and between-coefficient contrast masking of DCT

  basis functions (PSNR-HVS-M)



Example:



VQMT.exe original.yuv processed.yuv 1088 1920 250 1 results PSNR SSIM MSSSIM

VIFP



will create the following output files in CSV (comma-separated values) format:

- results_pnsr.csv

- results_ssim.csv

- results_msssim.csv

- results_vifp.csv



Notes:

- SSIM comes for free when MSSSIM is computed (but you still need to specify it

  to get the output)

- PSNRHVS and PSNRHVSM are always computed at the same time (but you still need

  to specify both to get the two outputs)

- When using MSSSIM, the height and width of the video have to be multiple of 16

- When using VIFP, the height and width of the video have to be multiple of 8



# COPYRIGHT



Permission is hereby granted, without written agreement and without license or

royalty fees, to use, copy, modify, and distribute the software provided and its

documentation for research purpose only, provided that this copyright notice and

the original authors' names appear on all copies and supporting documentation.

The software provided may not be commercially distributed. In no event shall the

Ecole Polytechnique Fédérale de Lausanne (EPFL) be liable to any party for

direct, indirect, special, incidental, or consequential damages arising out of

the use of the software and its documentation.

The Ecole Polytechnique Fédérale de Lausanne (EPFL) specifically disclaims any

warranties.

The software provided hereunder is on an "as is" basis and the Ecole

Polytechnique Fédérale de Lausanne (EPFL) has no obligation to provide

maintenance, support, updates, enhancements, or modifications.



# REFERENCES



- Z. Wang, A.C. Bovik, H.R. Sheikh, and E.P. Simoncelli, "Image quality

  assessment: from error visibility to structural similarity," IEEE

  Transactions on Image Processing, vol. 13, no. 4, pp. 600–612, April 2004.

- Z. Wang, E.P. Simoncelli, and A.C. Bovik, "Multiscale structural similarity

  for image quality assessment," in IEEE Asilomar Conference on Signals,

  Systems and Computers, November 2003, vol. 2, pp. 1398–1402.

- H.R. Sheikh and A.C. Bovik, "Image information and visual quality," IEEE

  Transactions on Image Processing, vol. 15, no. 2, pp. 430-444, February 2006.

- K. Egiazarian, J. Astola, N. Ponomarenko, V. Lukin, F. Battisti, and M.

  Carli, "New full-reference quality metrics based on HVS," in Proceedings of

  the Second International Workshop on Video Processing and Quality Metrics,

  2006.

- N. Ponomarenko, F. Silvestri, K. Egiazarian, M. Carli, J. Astola, and V.

  Lukin, "On between-coefficient contrast masking of DCT basis functions," in

  Proceedings of the Third International Workshop on Video Processing and

  Quality Metrics for Consumer Electronics, January 2007.