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MSU Quality Measurement Tool: Metrics information

MSU Graphics & Media Lab (Video Group)

 

PSNR

This metric, which is used often in practice, called peak-to-peak signal-to-noise ratio — PSNR.

Generally, this metric is equal to Mean Square Error, but it is more convenient to use because of logarithmic scale. It has the same disadvantages, as the MSE metric.
In this program you could calculate PSNR for all YUV and RGB components and for L component of LUV color space.

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Y-YUV PSNR
Y-YUV PSNR

Colors, in order of PSNR growing: red, yellow, green, blue, black

 

MSAD

The value of this metric is the mean absolute difference of the color components in the correspondent points of image. This metric is used for testing codecs and filters.

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MSAD
MSAD

 

Delta

The value of this metric is the mean difference of the color components in the correspondent points of image. This metric is used for testing codecs and filters.

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Delta
Delta

Red color Xij > Yij, green color Xij < Yij

 

Blurring Measure

This metric allows you to compare power of bluring of two images. If value of the metric for first picture is greater, than for second it means that second picture is more blurred, than first one.

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Blurring Measure
Blurring Measure

Red color - first image is more sharpen, than second. Green color - second image is sharpen, than first.

 

Blocking Measure

This metric was created to measure subjective blocking effect in video sequence. For example, in contrast areas of the frame blocking is not appreciable, but in smooth areas these edges are conspicuous. This metric also contains heuristic method for detecting objects edges, which are placed to the edge of the block. In this case metric value is pulled down, it allows to measure blocking more precisely. We use information from previous frames to achieve better accuracy.

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Blocking Measure
Blocking Measure

 

SSIM Index

SSIM Index is based on measuring of three components (luminance similarity, contrast similarity and structural similarity) and combining them into result value.
Original paper

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SSIM
SSIM

More bright areas corresponds to greater difference.

 

VQM

VQM uses DCT to correspond to human perception.
Original paper

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VQM
VQM

More bright blocks corresponds to greater difference.

 

MSE

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Y-YUV MSE
Y-YUV MSE

 

Information About YUV <=> RGB Tables

 

REC.601

This table is default YUV <=> RGB table in AVISynth.
{R [0...255], G [0...255], B [0...255]} => {Y [16...235], U [16...240], V [16...240]}
RGB to YUV

	Y = (0.257 * R) + (0.504 * G) + (0.098 * B) + 16 

	U = -(0.148 * R) - (0.291 * G) + (0.439 * B) + 128 

	V =  (0.439 * R) - (0.368 * G) - (0.071 * B) + 128 
		
YUV to RGB
	R = 1.164 * (Y - 16) + 1.596 * (V - 128)

	G = 1.164 * (Y - 16) - 0.391 * (U - 128) - 0.813 * (V - 128)

	B = 1.164 * (Y - 16) + 2.018 * (U - 128)
		

 

PC.601

{R [0...255], G [0...255], B [0...255]} => {Y [0...255], U [-128...128], V [-128...128]}
RGB to YUV

	Y = 0.299 * R + 0.587 * G + 0.114 * B

	U = -(0.147) * R - 0.289 * G + 0.436 * B

	V = 0.615 * R - 0.515 * G - 0.100 * B
		
YUV to RGB
	R = Y + 1.14 * V

	G = Y - 0.395 * U - 0.581 * V
			                             
	B = Y + 2.032 * U
		

 

YUV Files

YUV files form a variety of "raw data" files. Now MSU Video Quality Measurement Tool supports different types of them, but if you use .yuv files in your comparison note that

  1. We assumed, that U and V values in YUV files are positive.
  2. If you use any YUV<=>RGB table for creating YUV files from AVI (or AVI from YUV) in your program you must choose this table in the settings of MSU Video Quality Measurement Tool.

 

Download

See also MSU Video Quality Metric

e-mail: 

 

Other resources

Video resources:

Public MSU video filters
Here are available VirtualDub and AviSynth filters. Commonly we develop a whole family of some kind of a filter. Generally there are also versions optimized for PC and hardware implementations (ASIC/FPGA/DSP). These optimized versions can be licensed to companies. Please contact us for details via video(at)graphics.cs.msu_ru.