Improved Linearization of the Optimal Compression Function for Laplacian Source
, and | Jun 17, 2014
Published Online: Jun 17, 2014
Page range: 179 - 183
Received: Jul 25, 2011
DOI: https://doi.org/10.2478/jee-2014-0028
Keywords
© Faculty of Electrical Engineering and Information Technology, Slovak University of Technology
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In this paper, linearization of the optimal compression function is done and hierarchical coding (by coding the regions firstly and then the cells inside the region) is applied, achieving simple and fast process of coding and decoding. The signal at the entrance of the scalar quantizer is modeled by Laplacian probability density function. It is shown that the linearization of inner regions very little influences distortion and therefore only the last region should be optimized. Two methods of optimization of the last region are proposed, that improve performances of the scalar quantizer, and obtained SQNR (signal-to-quantization noise ratio) is close to that of the nonlinear optimal compression function.