JOURNAL ARTICLE

<title>Wavelet-based embedded zerotree extension to color coding</title>

Victoria T. Franques

Year: 1998 Journal:   Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE Vol: 3391 Pages: 26-36   Publisher: SPIE

Abstract

Recently, a new image compression algorithm was developed which employs wavelet transform and a simple binary linear quantization scheme with an embedded coding technique to perform data compaction. This new family of coder, Embedded Zerotree Wavelet (EZW), provides a better compression performance than the current JPEG coding standard for low bit rates. Since EZW coding algorithm emerged, all of the published coding results related to this coding technique are on monochrome images. In this paper the author has enhanced the original coding algorithm to yield a better compression ratio, and has extended the wavelet-based zerotree coding to color images. Color imagery is often represented by several components, such as RGB, in which each component is generally processed separately. With color coding, each component could be compressed individually in the same manner as a monochrome image, therefore requiring a threefold increase in processing time. Most image coding standards employ de-correlated components, such as YIQ or Y, CB, CR and subsampling of the 'chroma' components, such coding technique is employed here. Results of the coding, including reconstructed images and coding performance, will be presented.

Keywords:
Context-adaptive binary arithmetic coding Artificial intelligence RGB color model Computer vision JPEG 2000 Wavelet transform Computer science Monochrome Transform coding Variable-length code Data compression Coding (social sciences) Wavelet Image compression Tunstall coding Coding tree unit Mathematics Algorithm Image processing Decoding methods Discrete cosine transform Image (mathematics)

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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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