An analysis-compression technique for black and white documents

TitleAn analysis-compression technique for black and white documents
Publication TypeConference Paper
Year of Publication1996
AuthorsKossentini, F., and R. K. Ward
Conference NameImage Analysis and Interpretation, 1996., Proceedings of the IEEE Southwest Symposium on
Pagination141 -144
Date Publishedapr.
Keywordsadaptive arithmetic coding, adaptive codes, algorithm, analysis-compression technique, application-dependent analysis, approximation, bandwidth constraint, black and white documents, conditioning region of support, data compression, document image processing, experimental results, global statistics, high order statistical modeling, higher order statistics, image coding, input image, JBIG standard, local statistics, lossless compression, lossy compression, modeling techniques, output bit stream, performance, probability, progressive transmission, weighting coefficients

This paper presents an analysis and compression technique that can be used for both lossy and lossless compression of black and white documents simultaneously. It is assumed that an application-dependent analysis technique is employed to produce weighting coefficients that allow ordering of the bits according to their significance. Like the algorithm described in the JBIG standard, the proposed algorithm consists of high order statistical modeling and adaptive arithmetic coding. However, our modeling techniques are more sophisticated in the sense that they are adaptive both locally and globally. The conditioning region of support used for the generation of the states is determined based on the global statistics of the input image, and the states and associated probabilities are adapted to the local statistics. Moreover, our algorithm is naturally suitable for progressive transmission since the output bit stream can be truncated anywhere, leading to the best possible approximation given a bandwidth constraint. Experimental results reveal that the proposed algorithm not only achieves high near-lossless compression performance but also outperforms JBIG when used for lossless compression


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