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Proceedings Paper

Adaptive quantization in a perceptive uniform color space: an application to H.263 coding
Author(s): Gaetano Scarano; Stefania Colonnese; S. Pratico; Giuseppe Russo
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Paper Abstract

In this work we propose a method for adaptive quantization of motion compensation residuals, in an H.263 coding scheme, based on color information. In the proposed strategy, the perceptive distance between the original and the predicted version of each macroblock is evaluated in the perceptive uniform color space L, a, b. Exploiting the properties of the perceptive uniform color spaces, the color distance is easily evaluated by means of the Euclidean distance, and its average value is compared with a threshold in order to choose the suitable quantization. Simulation results show that the adaptive quantization is very efficient in reducing the bit-rate when the sequences exhibit slow regular motion, and the quantization performances are upper-bounded by the motion compensation performances. In fact, for sequences with low-medium amount of motion, the block-based motion compensation efficiently predicts the actual frame from adjacent ones and the residuals are due to noise, or to small color variations. Then, in these cases, the adaptive quantization can provide significant bit-rate reduction, without subjective quality degradation. The proposed strategy is strictly compatible with the H.263 coding standard; however it is quite general, and can be useful exploited in different coding frameworks, based on various motion compensation techniques, whenever motion compensation residuals are evaluated.

Paper Details

Date Published: 10 January 1997
PDF: 12 pages
Proc. SPIE 3024, Visual Communications and Image Processing '97, (10 January 1997); doi: 10.1117/12.263214
Show Author Affiliations
Gaetano Scarano, Univ. of Rome La Sapienza (Italy)
Stefania Colonnese, Fondazione Ugo Bordoni (Italy)
S. Pratico, Telecom Italy (Italy)
Giuseppe Russo, Fondazione Ugo Bordoni (Italy)

Published in SPIE Proceedings Vol. 3024:
Visual Communications and Image Processing '97
Jan Biemond; Edward J. Delp III, Editor(s)

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