JOURNAL ARTICLE

Parallel lossless image compression using Huffman and arithmetic coding

Abstract

The authors show that high-resolution images can be encoded and decoded efficiently in parallel. They present an algorithm based on the hierarchical multi-level progressive (MLP) method, used either with Huffman coding or with a new variant of arithmetic coding called quasi-arithmetic coding. The coding step can be parallelized, even though the codes for different pixels are of different lengths; parallelization of the prediction and error modeling components is straightforward.< >

Keywords:
Huffman coding Arithmetic coding Computer science Lossless compression Tunstall coding Coding (social sciences) Context-adaptive binary arithmetic coding Shannon–Fano coding Data compression Variable-length code Algorithm Pixel Arithmetic Image compression Theoretical computer science Artificial intelligence Image processing Mathematics Image (mathematics) Decoding methods

Metrics

32
Cited By
1.15
FWCI (Field Weighted Citation Impact)
13
Refs
0.84
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Algorithms and Data Compression
Physical Sciences →  Computer Science →  Artificial Intelligence
Advanced Data Compression Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Video Coding and Compression Technologies
Physical Sciences →  Computer Science →  Signal Processing

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