Medical image processing using novel wavelet filters based on atomic functions: Optimal medical image compression

Cristina Juarez Landin, Magally Martinez Reyes, Anabelem Soberanes Martin, Rosa Maria Valdovinos Rosas, Jose Luis Sanchez Ramirez, Volodymyr Ponomaryov, Maria Dolores Torres Soto

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

The analysis of different Wavelets including novel Wavelet families based on atomic functions are presented, especially for ultrasound (US) and mammography (MG) images compression. This way we are able to determine with what type of filters Wavelet works better in compression of such images. Key properties: Frequency response, approximation order, projection cosine, and Riesz bounds were determined and compared for the classic Wavelets W9/7 used in standard JPEG2000, Daubechies8, Symlet8, as well as for the complex Kravchenko-Rvachev Wavelets ψ(t) based on the atomic functions up(t), fup 2(t), and eup(t). The comparison results show significantly better performance of novel Wavelets that is justified by experiments and in study of key properties.

Original languageEnglish
Title of host publicationSoftware Tools and Algorithms for Biological Systems
EditorsHamid Arabnia, Quoc-Nam Tran
Pages497-504
Number of pages8
DOIs
StatePublished - 2011

Publication series

NameAdvances in Experimental Medicine and Biology
Volume696
ISSN (Print)0065-2598

Keywords

  • Atomic functions
  • Compression
  • Mammography images
  • Ultrasound images
  • Wavelet transform

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