JOURNAL ARTICLE

Fast variable run-length coding for embedded progressive wavelet-based image compression

Wilhelm BerghornTobias BoskampMarkus LangHeinz‐Otto Peitgen

Year: 2001 Journal:   IEEE Transactions on Image Processing Vol: 10 (12)Pages: 1781-1790   Publisher: Institute of Electrical and Electronics Engineers

Abstract

Run-length coding has attracted much attention in wavelet-based image compression because of its simplicity and potentially low complexity. The main drawback is the inferior RD-performance compared to the state-of-the-art-coder SPIHT. In this paper, we concentrate on the embedded progressive run-length code of Tian and Wells (1996, 1998). We consider significance sequences drawn from the scan in the dominant pass. It turns out that self-similar curves for scanning the dominant pass increase the compression efficiency significantly. This is a consequence of the correlation of direct neighbors in the wavelet domain. This dependence can be better exploited by using groups of coefficients, similar to the SPIHT algorithm. This results in a new and very fast coding algorithm, which shows performance similar to the state-of-the-art coder SPIHT, but with lower complexity and small and fixed memory overhead.

Keywords:
Set partitioning in hierarchical trees Wavelet Image compression Data compression Algorithm Wavelet transform Computer science Computational complexity theory Coding (social sciences) Variable-length code Shannon–Fano coding Mathematics Artificial intelligence Pattern recognition (psychology) Decoding methods Image (mathematics) Discrete wavelet transform Image processing Context-adaptive binary arithmetic coding Statistics

Metrics

22
Cited By
0.69
FWCI (Field Weighted Citation Impact)
27
Refs
0.76
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

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
Digital Filter Design and Implementation
Physical Sciences →  Computer Science →  Signal Processing

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