Abstract
This paper describes a two-stage method of document image compression wherein a grayscale document image is first processed to improve its compressibility, then losslessly compressed. The initial processing involves hierarchical, coarse-to-fine morphological operations designed to combat the noiselike variability of the low-order bits while attempting to preserve or even improve intelligibility. The result of this stage is losslessly compressed by an arithmetic coder that uses a mixture model to derive context-conditional graylevel probabilities. The lossless stage is compared experimentally with several reference methods, and is found to be competitive at all rates. The overall system is found to be comparable with JPEG in terms of mean-square error performance, but appears to outperform JPEG in terms of subjectively judged document image intelligibility.
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© 2002 Kluwer Academic/Plenum Publishers
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Popat, K., Bloomberg, D.S. (2002). Two-Stage Lossy/Lossless Compression of Grayscale Document Images. In: Goutsias, J., Vincent, L., Bloomberg, D.S. (eds) Mathematical Morphology and its Applications to Image and Signal Processing. Computational Imaging and Vision, vol 18. Springer, Boston, MA. https://doi.org/10.1007/0-306-47025-X_39
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DOI: https://doi.org/10.1007/0-306-47025-X_39
Publisher Name: Springer, Boston, MA
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