Compression of large binary images in digital spatial libraries

Eugene Jevgeni Ageenko; Pasi Franti

doi:10.1117/12.373562

23 December 1999 Compression of large binary images in digital spatial libraries

Eugene Jevgeni Ageenko, Pasi Franti

Proceedings Volume 3972, Storage and Retrieval for Media Databases 2000; (1999) https://doi.org/10.1117/12.373562
Event: Electronic Imaging, 2000, San Jose, CA, United States

Abstract

A method for lossless compression of large binary images is proposed for applications where spatial access to the image is needed. The method utilizes the advantages of (1) variable-size context modeling in a form of context trees, and (2) forward-adaptive statistical compression. New strategies for constructing the context tree are considered, including a fast two-stage bottom-up approach. The proposed technique achieves higher compression rates and allows dense tiling of images down to 50 X 50 pixels without sacrificing the compression performance. It enables partial decompression of large images far more efficiently than if the standard JBIG was applied.

Citation Download Citation

Eugene Jevgeni Ageenko and Pasi Franti "Compression of large binary images in digital spatial libraries", Proc. SPIE 3972, Storage and Retrieval for Media Databases 2000, (23 December 1999); https://doi.org/10.1117/12.373562

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