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Proceedings Paper

Applications of gain-spectral-block classification in image coding
Author(s): Hamid Jafarkhani; M. Kerry; Nariman Farvardin
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Paper Abstract

This work focuses on the development of a two-level image block classification scheme and its application to low bit rate image coding. Using this classifier, we present two adaptive encoding structures, one based on vector quantization (VQ) and the other based on transform coding. The first stage of our system classifies the image blocks into K1 classes based on the block grain, similar to the well-known classification scheme of Chen and Smith, but allows for the possibility of a variable number of vectors per class. To do this, we develop an iterative mini-max algorithm that adjusts the vectors among the classes so that the resulting mean-normalized standard deviation of the gain values within any class is similar to all other classes. After classifying based on block gain values, we further classify each gain-class into K2 spectral classes. This is accomplished by performing a 1D LPC-type analysis of each block, and clustering the resulting LPC vectors using a vector quantizer (VQ) with K2 codevectors. In order to make this spectral matching meaningful, the VQ is designed and implemented using the Itakura-Saito distortion measure. The resulting two-level classification scheme thus classifies an image into K equals K1K2 classes. A system consisting of a bank of K fixed-rate Multi-Stage VQ's and a DCT based system are then used to examine the usefulness of the proposed approaches for classification.

Paper Details

Date Published: 3 March 1995
PDF: 12 pages
Proc. SPIE 2418, Still-Image Compression, (3 March 1995); doi: 10.1117/12.204119
Show Author Affiliations
Hamid Jafarkhani, Univ. of Maryland/College Park (United States)
M. Kerry, Univ. of Maryland/College Park (United States)
Nariman Farvardin, Univ. of Maryland/College Park (United States)


Published in SPIE Proceedings Vol. 2418:
Still-Image Compression
Majid Rabbani; Edward J. Delp; Sarah A. Rajala, Editor(s)

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