A new nonlinear quantizer for image processing within nonextensive statistics

KILIÇ İ., Kayacan O.

Physica A: Statistical Mechanics and its Applications, vol.381, no.1-2, pp.420-430, 2007 (SCI-Expanded, Scopus) identifier identifier

  • Publication Type: Article / Article
  • Volume: 381 Issue: 1-2
  • Publication Date: 2007
  • Doi Number: 10.1016/j.physa.2007.03.028
  • Journal Name: Physica A: Statistical Mechanics and its Applications
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Page Numbers: pp.420-430
  • Keywords: image processing, nonlinear quantization, Tsallis statistics
  • Manisa Celal Bayar University Affiliated: Yes

Abstract

In this study, we introduce a new nonlinear quantizer for image processing by using Tsallis entropy. Lloyd-Max quantizer is commonly used in minimizing the quantization errors. We report that the new introduced technique works better than Lloyd-Max one for selected standard images and could be an alternative way to minimize the quantization errors for image processing. We, therefore, hopefully expect that the new quantizer could be a useful tool for all the remaining process after image quantization, such as coding (lossy and lossless compression). © 2007 Elsevier B.V. All rights reserved.