Abstract
This paper presents a qualitative approach of combining Golomb-Rice (GR) code with algebraic bijective mappings which losslessly convert between arbitrary positive integers of different dimension and shape the distribution of generalized Gaussian sources. The mappings, integer nesting and splitting, enables GR encoding, with a little additional computation, to compress more efficiently sources based on wider classes of distributions than Laplacian. Simulations showed, especially for some Gaussian sources, almost optimal average code length can be achievable by performing integer nesting before GR encoding the integers. This scheme will be useful for applications dealing with various types of sources and requiring low computational costs.
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