Smooth image segmentation via multiresolution analysis

Jing Zhou, Xiang Fang, Bijoy K. Ghosh

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

2 Scopus citations

Abstract

In this paper, the problem of segmentation of smooth images has been studied using multiresolution analysis. The approximated image intensity function is modeled as a quadratic polynomial with additive noise within local windows. The analysis has been carried out with the aid of a new orthonormal wavelet basis introduced in this paper. A procedure has been developed to approximate an image at a coarse resolution by dropping the components of the image in such a way that small bumps at finer resolutions are suppressed. An image segmentation scheme is proposed. It performs initial segmentation on a coarse approximation of the image, and then updates the segments of the image at a finer resolution. The proposed algorithm has been tested on a variety of real images such as human faces, natural scenes, and medical images.

Original languageEnglish
Title of host publicationProceedings of SPIE - The International Society for Optical Engineering
PublisherSociety of Photo-Optical Instrumentation Engineers
Pages462-472
Number of pages11
ISBN (Print)0819416274
StatePublished - 1994
EventWavelet Applications in Signal and Image Processing II - San Diego, CA, USA
Duration: Jul 27 1994Jul 29 1994

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
Volume2303
ISSN (Print)0277-786X

Conference

ConferenceWavelet Applications in Signal and Image Processing II
CitySan Diego, CA, USA
Period07/27/9407/29/94

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