Paper
9 January 1998 Time-varying subband image coding with efficient reduction of higher-order redundancy
Benoit Maison, Luc Vandendorpe
Author Affiliations +
Proceedings Volume 3309, Visual Communications and Image Processing '98; (1998) https://doi.org/10.1117/12.298318
Event: Photonics West '98 Electronic Imaging, 1998, San Jose, CA, United States
Abstract
A region-adaptive subband coding algorithm is studied. The shape of the regions is not given beforehand, but is the result of a joint optimization with the set of coding operators. A simple space-varying M x M-band subband decomposition technique with instantaneous switching is utilized so that each M by M image block can be allocated to one of N concurrent encoders. The joint optimization is iterative and switches back and forth between optimization of the region shapes and of the coding operators defined by a set of subband filters and entropy coding tables ( quantization is uniform and constant) . From an information theoretic viewpoint, this procedure corresponds to the modeling of higher order redundancy by means offinite multidimensionalmixtures. The algorithm is tested on natural images and several conclusions are drawn. Region-adaptive coding presents a significant advantage compared to the equivalent single coder system. Although the optimal regions exhibit a distinctive structure, it is very different from any high level object-based segmentation. Finally, the efficiency of the approach lies mainly in its region-adaptive entropy coding capability. Adaptation of the transform operator itself appears to be less important. Keywords: Image Compression, Subband Coding, Adaptive, Mixture Distributions, HOS, Nonlinear Modeling
© (1998) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Benoit Maison and Luc Vandendorpe "Time-varying subband image coding with efficient reduction of higher-order redundancy", Proc. SPIE 3309, Visual Communications and Image Processing '98, (9 January 1998); https://doi.org/10.1117/12.298318
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KEYWORDS
Computer programming

Image segmentation

Image compression

Image filtering

Quantization

Statistical modeling

Electronic filtering

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