CVQE: a metric for continuous video quality evaluation at low bit rates

Many current quality evaluation models were designed to produce a single estimate of perceived quality for a video sequence coded at relatively high rates. These metrics perform a multi-channel decomposition to simulate the processes of the Human Visual System (HVS), followed by a distortion pooling stage that collapses the channels over frequency, time and space. Estimating quality at short intervals over the length of a video sequence, however, may be more useful for long video sequences than a single estimate, particularly in such applications as two pass video coding and video quality monitoring. This paper presents an objective metric designed to perform this task on video sequences coded at low bit rates. The metric implements a wavelet transform-based model of the human visual system and a method of temporal error pooling suited to continuous estimation of perceived quality. A time series distance metric based on piecewise linear representations is also introduced in order to quantify performance. The metric is evaluated on a wide range of low bit rate video content and shown to perform well in terms of the shape and overall mean of the output perceived quality waveform.

[1]  Edward H. Adelson,et al.  The Laplacian Pyramid as a Compact Image Code , 1983, IEEE Trans. Commun..

[2]  Peter G. J. Barten The Square Root Integral (SQRI): A New Metric To Describe The Effect Of Various Display Parameters On Perceived Image Quality , 1989, Photonics West - Lasers and Applications in Science and Engineering.

[3]  R. F. Hess,et al.  Temporal properties of human visual filters: number, shapes and spatial covariation , 1992, Vision Research.

[4]  Huib de Ridder Minkowski-metrics as a combination rule for digital-image-coding impairments , 1992 .

[5]  Geoffrey M. Boynton,et al.  New model of human luminance pattern vision mechanisms: analysis of the effects of pattern orientation, spatial phase, and temporal frequency , 1994, Other Conferences.

[6]  Patrick C. Teo,et al.  Perceptual image distortion , 1994, Proceedings of 1st International Conference on Image Processing.

[7]  William T. Freeman,et al.  Presented at: 2nd Annual IEEE International Conference on Image , 1995 .

[8]  C. Lambrecht Perceptual models and architectures for video coding applications , 1996 .

[9]  B. Wandell,et al.  Pattern—color separable pathways predict sensitivity to simple colored patterns , 1996, Vision Research.

[10]  C.-C. Jay Kuo,et al.  Image quality measurement using the Haar wavelet , 1997, Optics & Photonics.

[11]  John D. Villasenor,et al.  Visibility of wavelet quantization noise , 1997, IEEE Transactions on Image Processing.

[12]  J A Solomon,et al.  Model of visual contrast gain control and pattern masking. , 1997, Journal of the Optical Society of America. A, Optics, image science, and vision.

[13]  Don E. Pearson,et al.  Viewer response to time-varying video quality , 1998, Electronic Imaging.

[14]  Gary W. Meyer,et al.  A perceptually based adaptive sampling algorithm , 1998, SIGGRAPH.

[15]  Andrew B. Watson,et al.  Toward a perceptual video-quality metric , 1998, Electronic Imaging.

[16]  M. Ghanbari,et al.  An objective measurement tool for MPEG video quality , 1998, Signal Process..

[17]  Andrew P. Bradley,et al.  A wavelet visible difference predictor , 1999, IEEE Trans. Image Process..

[18]  Jeffrey B. Mulligan,et al.  Design and performance of a digital video quality metric , 1999, Electronic Imaging.

[19]  Stefan Winkler,et al.  Perceptual distortion metric for digital color video , 1999, Electronic Imaging.

[20]  A. M. Rohaly,et al.  Comparison of temporal pooling methods for estimating the quality of complex video sequences , 1999, Electronic Imaging.

[21]  H. R. Wu,et al.  Human visual system based objective digital video quality metrics , 2000, WCC 2000 - ICSP 2000. 2000 5th International Conference on Signal Processing Proceedings. 16th World Computer Congress 2000.

[22]  Stefan Winkler,et al.  Quality metric design: a closer look , 2000, Electronic Imaging.

[23]  Yan Yang,et al.  Generalized rate-distortion optimization for motion-compensated video coders , 2000, IEEE Trans. Circuits Syst. Video Technol..

[24]  Eamonn J. Keogh,et al.  An online algorithm for segmenting time series , 2001, Proceedings 2001 IEEE International Conference on Data Mining.

[25]  Sheila S. Hemami,et al.  Subjective quality evaluation of low-bit-rate video , 2001, IS&T/SPIE Electronic Imaging.

[26]  Zhenghua Yu,et al.  Vision-model-based impairment metric to evaluate blocking artifacts in digital video , 2002, Proc. IEEE.