1 January 2001 Digital video quality metric based on human vision
Andrew B. Watson, Quingmin J. Hu, John F. McGowan III
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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.
©(2001) Society of Photo-Optical Instrumentation Engineers (SPIE)
Andrew B. Watson, Quingmin J. Hu, and John F. McGowan III "Digital video quality metric based on human vision," Journal of Electronic Imaging 10(1), (1 January 2001). https://doi.org/10.1117/1.1329896
Published: 1 January 2001
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Cited by 303 scholarly publications and 24 patents.
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KEYWORDS
Video

Data modeling

Visualization

Video compression

Quantization

Human vision and color perception

Error analysis

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