Effect of wavelet filters on SFQ encoder performance for medical images

Krishna Kumar, Rajeev Gupta, Basant Kumar, Chandrahas Kumar

Research output: Chapter in Book/Report/Conference proceedingPaper in conference proceedingpeer-review

Abstract

This paper is focused on analysing the effect of wavelet filters on Space frequency quantization (SFQ) coder performance. SFQ is a new class of image coding algorithms coupling standard scalar quantization of frequency coefficients with tree-structured quantization (related to spatial structures) has attracted wide attention because its good performance appears to confirm the promised efficiencies of hierarchical representation [1]. It has been shown that the statistics of wavelet coefficients in the medical images can be better approximated by the Generalized Pareto distribution (for positive DWT coefficients) and Generalized Student-t distribution (for negative DWT coefficients) [2]. To analyze the performance of SFQ coder with different wavelet filters PSNR (peak signal to noise ratio) is measured at various compression rates.

Original languageEnglish
Title of host publication2015 38th International Conference on Telecommunications and Signal Processing, TSP 2015
EditorsKarol Molnar, Norbert Herencsar
PublisherIEEE - Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781479984985
DOIs
Publication statusPublished - 2015 Oct 9
Externally publishedYes
Event2015 38th International Conference on Telecommunications and Signal Processing, TSP 2015 - Prague, Czech Republic
Duration: 2015 Jul 92015 Jul 11

Publication series

Name2015 38th International Conference on Telecommunications and Signal Processing, TSP 2015

Conference

Conference2015 38th International Conference on Telecommunications and Signal Processing, TSP 2015
Country/TerritoryCzech Republic
CityPrague
Period2015/07/092015/07/11

Bibliographical note

Publisher Copyright:
© 2015 IEEE.

Subject classification (UKÄ)

  • Medical Imaging

Free keywords

  • Medical Image Compression
  • SFQ
  • Wavelet Transforms

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