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Published October 1999 | public
Journal Article Open

Weighted universal image compression


We describe a general coding strategy leading to a family of universal image compression systems designed to give good performance in applications where the statistics of the source to be compressed are not available at design time or vary over time or space. The basic approach considered uses a two-stage structure in which the single source code of traditional image compression systems is replaced with a family of codes designed to cover a large class of possible sources. To illustrate this approach, we consider the optimal design and use of two-stage codes containing collections of vector quantizers (weighted universal vector quantization), bit allocations for JPEG-style coding (weighted universal bit allocation), and transform codes (weighted universal transform coding). Further, we demonstrate the benefits to be gained from the inclusion of perceptual distortion measures and optimal parsing. The strategy yields two-stage codes that significantly outperform their single-stage predecessors. On a sequence of medical images, weighted universal vector quantization outperforms entropy coded vector quantization by over 9 dB. On the same data sequence, weighted universal bit allocation outperforms a JPEG-style code by over 2.5 dB. On a collection of mixed test and image data, weighted universal transform coding outperforms a single, data-optimized transform code (which gives performance almost identical to that of JPEG) by over 6 dB.

Additional Information

© Copyright 1999 IEEE. Reprinted with permission. Manuscript received January 7, 1997; revised January 15, 1999. This work was presented in part at the 1994 IEEE Data Compression Conference, the 1995 IEEE International Conference on Acoustics, Speech, and Signal Processing, and the 1995 IEEE International Conference on Image Processing. This work was supported in part by the National Science Foundtion under Grant MIP-9501977, by a Bell Laboratories Ph.D. Scholarship, and by a grant from the Center for Telecommunications at Stanford University. The associate editor coordinating the review of this manuscript and approving it for publication was Dr. Roland Wilson.


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