JOURNAL ARTICLE

Entropy coded successively refinable uniform threshold quantizers

Abstract

We examine the performance of entropy coded successively refinable uniform threshold quantizers, which have been utilized in numerous proposed progressive image coders. We view a successively refinable quantizer with N stages of refinement as consisting of a sequence of partitions {P/sup n/}, and a sequence of codebooks {C/sup n/}, 1/spl les/n/spl les/N. We denote the n/sup th/ reconstruction of an input sample x as x/sup n/; it can be obtained using the n/sup th/ partition and n/sup th/ codebook and a simple quantization rule. We consider the design of entropy-coded successively refinable scalar quantizers in which the finest (highest rate) partition and corresponding codebook comprise a uniform threshold quantizer (UTQ). All codebooks are designed optimally for the corresponding partitions and it is well known that entropy coded UTQs perform within 0.255 bits/sample of the rate distortion bound for a variety of source distributions.

Keywords:
Codebook Mathematics Entropy (arrow of time) Algorithm Upper and lower bounds Rate–distortion theory Quantization (signal processing) Partition (number theory) Discrete mathematics Combinatorics Data compression Mathematical analysis Physics

Metrics

4
Cited By
0.68
FWCI (Field Weighted Citation Impact)
2
Refs
0.71
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Topics

Advanced Data Compression Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Image and Signal Denoising Methods
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Image Enhancement Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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