Data compression via alphabet partitioning and group partitionin

Coded data generation or conversion – Digital code to digital code converters – To or from code based on probability

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H03M 700

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059595604

ABSTRACT:
A data compression method, system and program code are provided which optimize entropy-coding by reducing complexity through alphabet partitioning, and then employing sample-group partitioning in order to maximize data compression on groups of source numbers. The approach is to employ probabilities to renumber source numbers so that smaller numbers correspond to more probable source numbers. This is followed by group partitioning of the stream of resultant numbers into at least two groups, for example, defining regions of an image, ranges of time, or a linked list of data elements related by spatial, temporal or spatio-temporal dependence. A maximum number (N.sub.m) is found in a group of numbers of the at least two groups and then entropy-coded. A recursive entropy encoding of the numbers of the group is then employed using the maximum number N.sub.m. The process is repeated for each partitioned group. Decoding of the resultant codewords involves the inverse process. Transformation and/or quantization may all be employed in combination with the group-partitioning entropy encoding.

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