System and method for lossless image compression having improved

Facsimile and static presentation processing – Facsimile – Reduced time or bandwidth for static image communication

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358426, 358470, 3582612, 382238, 382239, 382252, 341 65, H04N 1417, H04N 141, G06K 936

Patent

active

057643741

ABSTRACT:
A lossless image compression encoder/decoder system having a context determination circuit and a code generator. The image compressor uses the context of a pixel to be encoded to predict the value of the pixel and determines a prediction error and maps the prediction error to a mapped value having a distribution suitable for Golomb encoding. The image compressor contains a context quantizer that quantizes the context of pixels. The image compressor determines a Golomb parameter based on the context and historical information gathered during the coding of an image. To avoid systematic prediction biases in an image, the image compressor adjusts the distribution of prediction residuals to a distribution suitable for Golomb coding. As it encodes a particular pixel, the encoder uses the Golomb parameter to determine a Golomb code for the prediction error and encodes that value. To decompress an image, the decompressor determines and quantizes the context of each pixel being decoded. The decompressor uses the same pixels as the compressor to determine the context. The decompressor uses the context and historical information gathered during the decompression of the image to determine a Golomb parameter for the context in which the pixel occured. The decompressor retrieves from the compressed image the code for the pixel. Using the Golomb parameter and the retrieved code, the decompressor determines the mapped value of the code. The decompressor then uses the inverse mapping to determine the error value. The decompressor uses a predictor to predict the value of the pixel based on the context and adds the error value to determine the actual value of the pixel. In one embodiment the image compressor uses an alphabet extension, embedded in its context model, in specific low gradient contexts to reduce the redundancy of the encoding.
Other systems and methods are disclosed.

REFERENCES:
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patent: 5680129 (1997-10-01), Weinberger et al.
M. J. Weinberger, G. Seroussi, and G. Sapiro, "LOCO 2 I: A low complexity, Context-Based, Lossless Image Compression Algorithm," Tech. Rep. HPL-95-62, Hewlett-Packard Laboratories, Jun. 1995.
S. W. Golomb, "Run-length encodings," IEEE Trans. Inform. Theory, vol. IT-12, pp. 399-401, Jul. 1966.
R. Gallager and D. C. V. Voorhis, "Optimal source codes for geometrically distributed integer alphabets," IEEE Trans. Inform. Theory, vol. IT-21, pp. 228-230, Mar. 1975.
R. F. Rice, "Some practical universal noiseless coding techniques," Tech. Rep. Publication 79-22, JPL, Mar. 1979.
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