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Adaptive mammographic image feature enhancement using wavelet-based multiresolution analysis

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

4 Scopus citations

Abstract

This paper presents a novel and computationally efficient approach to an adaptive mammographic image feature enhancement using wavelet-based multiresolution analysis. Upon wavelet decomposition applied to a given mammographic image, we integrate the information of the tree-structured zerocrossings of wavelet coefficients and the information of the low-pass filtered subimage to enhance the desired image features. A discrete wavelet transform with pyramidal structure has been employed to speed up the computation for wavelet decomposition and reconstruction. The spatio-frequency localization property of the wavelet transform is exploited based on the spatial coherence of image and the principle of human psychovisual mechanism. Preliminary results show that the proposed approach is able to adaptively enhance local edge features, suppress noise, and improve global visualization of mammographic image features. This wavelet-based multiresolution analysis is therefore promising for computerized mass screening of mammograms.

Original languageEnglish
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
EditorsHarold H. Szu
Pages400-411
Number of pages12
StatePublished - 1996
EventWavelet Applications III - Orlando, FL, USA
Duration: Apr 8 1996Apr 12 1996

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume2762

Conference

ConferenceWavelet Applications III
CityOrlando, FL, USA
Period04/8/9604/12/96

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