Adaptive vector quantization for binary images

Rustin W. Allred; Richard W. Christiansen; Douglas M. Chabries

doi:10.1117/12.411536

28 December 2000 Adaptive vector quantization for binary images

Rustin W. Allred, Richard W. Christiansen, Douglas M. Chabries

Proceedings Volume 4115, Applications of Digital Image Processing XXIII; (2000) https://doi.org/10.1117/12.411536
Event: International Symposium on Optical Science and Technology, 2000, San Diego, CA, United States

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.

Citation Download Citation

Rustin W. Allred, Richard W. Christiansen, and Douglas M. Chabries "Adaptive vector quantization for binary images", Proc. SPIE 4115, Applications of Digital Image Processing XXIII, (28 December 2000); https://doi.org/10.1117/12.411536

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