Paper
23 June 2003 No-reference quality metric for degraded and enhanced video
Author Affiliations +
Proceedings Volume 5150, Visual Communications and Image Processing 2003; (2003) https://doi.org/10.1117/12.510112
Event: Visual Communications and Image Processing 2003, 2003, Lugano, Switzerland
Abstract
In this paper we present a no-reference objective quality metric (NROQM) that has resulted from extensive research on impairment metrics, image feature metrics, and subjective image quality in several projects in Philips Research, and participation in the ITU Video Quality Experts Group. The NROQM is aimed at requirements including video algorithm development, embedded monitoring and control of image quality, and evaluation of different types of display systems. NROQM is built from metrics for desirable and non-desirable image features (sharpness, contrast, noise, clipping, ringing, and blocking artifacts), and accounts for their individual and combined contributions to perceived image quality. We describe our heuristic, incremental approach to modeling quality and training the NROQM, and its advantages to deal with imperfect data and imperfect metrics. The results of training the NROQM using a large set of video sequences, which include degraded and enhanced video, show high correlation between objective and subjective scores, and the results of the first performance test show good objective-subjective correlations as well. We also discuss issues that require further research such as fully content-independent metrics, measuring over-enhanced video quality, and the role of temporal impairment metrics.
© (2003) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jorge E. Caviedes and Franco Oberti "No-reference quality metric for degraded and enhanced video", Proc. SPIE 5150, Visual Communications and Image Processing 2003, (23 June 2003); https://doi.org/10.1117/12.510112
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Cited by 42 scholarly publications.
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KEYWORDS
Video

Image quality

Critical dimension metrology

Image enhancement

Data modeling

Image processing

Video processing

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