<abstract xmlns="http://www.w3.org/1999/xhtml"><p> 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.</p></abstract>

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.

Improved Linearization of the Optimal Compression Function for Laplacian Source

Faculty of Electronic Engineering Nis, Aleksandra Medvedeva 14, 18000 Nis, Serbia

Journal of Electrical Engineering

This article is distributed under the terms of the Creative Commons Attribution Non-Commercial License, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

{"article-title":"Improved Linearization of the Optimal Compression Function for Laplacian Source"}

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...

Improved Linearization of the Optimal Compression Function for Laplacian Source

Publié en ligne: 17 juin 2014

Pages: 179 - 183

Reçu: 25 juil. 2011

DOI: https://doi.org/10.2478/jee-2014-0028

Mots clés
linearization, optimal compression function, scalar compandor

© Faculty of Electrical Engineering and Information Technology, Slovak University of Technology

This article is distributed under the terms of the Creative Commons Attribution Non-Commercial License, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Improved Linearization of the Optimal Compression Function for Laplacian Source

Publié en ligne: 17 juin 2014

Pages: 179 - 183

Reçu: 25 juil. 2011

DOI: https://doi.org/10.2478/jee-2014-0028

Mots cléslinearization, optimal compression function, scalar compandor

© Faculty of Electrical Engineering and Information Technology, Slovak University of Technology

This article is distributed under the terms of the Creative Commons Attribution Non-Commercial License, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Mots clés
linearization, optimal compression function, scalar compandor