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Proceedings Paper

Metrics to estimate image quality in compressed video sequences
Author(s): Gary O'Brien; Steven A. Israel; John M. Irvine; Charles Fenimore; John Roberts; Michelle Brennan; David Cannon; James Miller
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Paper Abstract

A fundamental problem in image processing is finding objective metrics that parallel human perception of image quality. In this study, several metrics were examined to quantify compression algorithms in terms of perceived loss of image quality. In addition, we sought to describe the relationship of image quality as a function of bit rate. The compression schemes used were JPEG2000, MPEG2, and H.264. The frame size was fixed at 848x480 and the encoding varied from 6000 k bps to 200 k bps. The metrics examined were peak signal to noise ratio (PSNR), structural similarity (SSIM), edge localization metrics, and a blur metric. To varying degrees, the metrics displayed desirable properties, namely they were monotonic in the bit rate, the group of pictures (GOP) structure could be inferred, and they tended to agree with human perception of quality degradations. Additional work is being conducted to quantify the sensitivity of these measures with respect to our Motion Imagery Quality Scale.

Paper Details

Date Published: 30 April 2007
PDF: 10 pages
Proc. SPIE 6546, Airborne Intelligence, Surveillance, Reconnaissance (ISR) Systems and Applications IV, 65460A (30 April 2007); doi: 10.1117/12.718718
Show Author Affiliations
Gary O'Brien, Science Applications International Corp. (United States)
Steven A. Israel, Science Applications International Corp. (United States)
John M. Irvine, Science Applications International Corp. (United States)
Charles Fenimore, National Institute of Standards and Technology (United States)
John Roberts, National Institute of Standards and Technology (United States)
Michelle Brennan, Moriarty and Associates (United States)
David Cannon, Science Applications International Corp. (United States)
James Miller, Science Applications International Corp. (United States)


Published in SPIE Proceedings Vol. 6546:
Airborne Intelligence, Surveillance, Reconnaissance (ISR) Systems and Applications IV
Daniel J. Henry, Editor(s)

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