JOURNAL ARTICLE

<title>Adaptive vector quantization for binary images</title>

Rustin W. AllredR.W. ChristiansenDouglas M. Chabries

Year: 2000 Journal:   Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE Vol: 4115 Pages: 113-120   Publisher: SPIE

Abstract

This paper describes a vector quantization variant for lossy compression of binary images. This algorithm, adaptive binary vector quantization for binary images (ABVQ), uses a novel, doubly-adaptive codebook to minimize error while typically achieving compression higher than is achieved by lossless techniques. ABVQ provides sufficient fidelity to be used on text images, line drawings, graphics, or any other binary (two-tone, or bi-level) images. Experimental results are included in the paper.

Keywords:
Vector quantization Codebook Linde–Buzo–Gray algorithm Lossless compression Lossy compression Binary number Quantization (signal processing) Computer science Artificial intelligence Fidelity Algorithm Data compression Computer vision Mathematics Arithmetic

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Topics

Advanced Data Compression Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Vision and Imaging
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Image and Video Retrieval Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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