Perceptually optimized quantization tables for H.264/AVC

Heng Chen; Geert Braeckman; Joeri Barbarien; Adrian Munteanu; Peter Schelkens

doi:10.1117/12.862738

7 September 2010 Perceptually optimized quantization tables for H.264/AVC

Heng Chen, Geert Braeckman, Joeri Barbarien, Adrian Munteanu, Peter Schelkens

Proceedings Volume 7798, Applications of Digital Image Processing XXXIII; 77981F (2010) https://doi.org/10.1117/12.862738
Event: SPIE Optical Engineering + Applications, 2010, San Diego, California, United States

Abstract

The H.264/AVC video coding standard currently represents the state-of-the-art in video compression technology. The initial version of the standard only supported a single quantization step size for all the coefficients in a transformed block. Later, support for custom quantization tables was added, which allows to independently specify the quantization step size for each coefficient in a transformed block. In this way, different quantization can be applied to the highfrequency and low-frequency coefficients, reflecting the human visual system's different sensitivity to high-frequency and low-frequency spatial variations in the signal. In this paper, we design custom quantization tables taking into account the properties of the human visual system as well as the viewing conditions. Our proposed design is based on a model for the human visual system's contrast sensitivity function, which specifies the contrast sensitivity in function of the spatial frequency of the signal. By calculating the spatial frequencies corresponding to each of the transform's basis functions, taking into account viewing distance and dot pitch of the screen, the sensitivity of the human visual system to variations in the transform coefficient corresponding to each basis function can be determined and used to define the corresponding quantization step size. Experimental results, whereby the video quality is measured using VQM, show that the designed quantization tables yield improved performance compared to uniform quantization and to the default quantization tables provided as a part of the reference encoder.

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Heng Chen, Geert Braeckman, Joeri Barbarien, Adrian Munteanu, and Peter Schelkens "Perceptually optimized quantization tables for H.264/AVC", Proc. SPIE 7798, Applications of Digital Image Processing XXXIII, 77981F (7 September 2010); https://doi.org/10.1117/12.862738

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KEYWORDS

Quantization

Visual system

Matrices

Contrast sensitivity

Computer programming

Visual process modeling

Visualization

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