Paper
3 June 1997 Test patterns and quality metrics for digital video compression
Charles P. Fenimore, Bruce F. Field, Craig Van Degrift
Author Affiliations +
Proceedings Volume 3016, Human Vision and Electronic Imaging II; (1997) https://doi.org/10.1117/12.274522
Event: Electronic Imaging '97, 1997, San Jose, CA, United States
Abstract
Lossy video compression systems such as MPEG2 introduce picture impairments such as image blocking, color distortion and persistent color fragments, 'mosquito noise,' and blurring in their outputs. While there are video test clips which exhibit one or more of these distortions upon coding, there is need of a set of well-characterized test patterns and video quality metrics. Digital test patterns can deliver calibrated stresses to specific features of the encoder, much as the test patterns for analog video stress critical characteristics of that system. Metrics quantify the error effects of compression by a computation. NIST is developing such test patterns and metrics for compression rates that typically introduce perceptually negligible artifacts, i.e. for high quality video. The test patterns are designed for subjective and objective evaluation. The test patterns include a family of computer-generated spinning wheels to stress luminance-based macro-block motion estimation algorithms and images with strongly directional high-frequency content to stress quantization algorithms. In this paper we discuss the spinning wheel test pattern. It has been encoded at a variety of bit rates near the threshold for the perception of impairments. We have observed that impairment perceptibility depends on the local contrast. For the spinning wheel we report the contrast at the threshold for perception of impairments as a function of the bit rate. To quantify perceptual image blocking we have developed a metric which detects 'flats:' image blocks of constant (or near constant) luminance. The effectiveness of this metric is appraised.
© (1997) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Charles P. Fenimore, Bruce F. Field, and Craig Van Degrift "Test patterns and quality metrics for digital video compression", Proc. SPIE 3016, Human Vision and Electronic Imaging II, (3 June 1997); https://doi.org/10.1117/12.274522
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Cited by 6 scholarly publications.
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KEYWORDS
Sensors

Video

Video compression

Computer programming

Motion estimation

Image compression

Quantization

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