Lossy compression of gray-scale document images by adaptive-offset quantization

Kris Popat

doi:10.1117/12.410832

21 December 2000 Lossy compression of gray-scale document images by adaptive-offset quantization

Kris Popat

Proceedings Volume 4307, Document Recognition and Retrieval VIII; (2000) https://doi.org/10.1117/12.410832
Event: Photonics West 2001 - Electronic Imaging, 2001, San Jose, CA, United States

Abstract

This paper describes an adaptive-offset quantization scheme and considers its application to the lossy compression of grayscale document images. The technique involves scalar- quantizing and entropy-coding pixels sequentially, such that the quantizer's offset is always chosen to minimize the expected number of bits emitted for each pixel, where the expectation is based on the predictive distribution used for entropy coding. To accomplish this, information is fed back from the entropy coder's statistical modeling unit to the quantizer. This feedback path is absent in traditional compression schemes. Encouraging but preliminary experimental results are presented comparing the technique with JPEG and with fixed-offset quantization on a scanned grayscale text image.

Citation Download Citation

Kris Popat "Lossy compression of gray-scale document images by adaptive-offset quantization", Proc. SPIE 4307, Document Recognition and Retrieval VIII, (21 December 2000); https://doi.org/10.1117/12.410832

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