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Journal of Electronic Imaging

Digital video quality metric based on human vision
Author(s): Andrew B. Watson; Quingmin J. Hu; John F. McGowan
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Paper Abstract

The growth of digital video has given rise to a need for computational methods for evaluating the visual quality of digital video. We have developed a new digital video quality metric, which we call DVQ (digital video quality) [A. B. Watson, in Human Vision, Visual Processing, and Digital Display VIII, Proc. SPIE 3299, 139– 147 (1998)]. Here, we provide a brief description of the metric, and give a preliminary report on its performance. DVQ accepts a pair of digital video sequences, and computes a measure of the magnitude of the visible difference between them. The metric is based on the discrete cosine transform. It incorporates aspects of early visual processing, including light adaptation, luminance, and chromatic channels; spatial and temporal filtering; spatial frequency channels; contrast masking; and probability summation. It also includes primitive dynamics of light adaptation and contrast masking. We have applied the metric to digital video sequences corrupted by various typical compression artifacts, and compared the results to quality ratings made by human observers.

Paper Details

Date Published: 1 January 2001
PDF: 10 pages
J. Electron. Imag. 10(1) doi: 10.1117/1.1329896
Published in: Journal of Electronic Imaging Volume 10, Issue 1
Show Author Affiliations
Andrew B. Watson, NASA Ames Research Ctr. (United States)
Quingmin J. Hu, NASA Ames Research Ctr. (United States)
John F. McGowan, NASA Ames Research Ctr. (United States)


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