A probabilistic image model for smoothing and compression

C. H. Li, Pong Chi YUEN, P. K.S. Tam

Research output: Chapter in book/report/conference proceedingConference contributionpeer-review

Abstract

In this paper, the problem of edge preserving smoothing in image processing is tackled by combining a noise corruption model and a region and edge image model. The derivation of the probability model for the first order difference in the gray levels of the region pixels and edge pixels leads to a non-linear filter with coefficients as functions of the estimated noise variance and edge intensity. Such a model-based approach allows the design of improved filters for noise filtering and image compression. Experimental results demonstrate the improved performance of the filter for both synthetic and natural images.

Original languageEnglish
Title of host publicationProceedings - International Conference on Information Technology
Subtitle of host publicationCoding and Computing, ITCC 2000
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages36-41
Number of pages6
ISBN (Electronic)0769505406, 9780769505404
DOIs
Publication statusPublished - 2000
Event1st International Conference on Information Technology: Coding and Computing, ITCC 2000 - Las Vegas, United States
Duration: 27 Mar 200029 Mar 2000

Publication series

NameProceedings - International Conference on Information Technology: Coding and Computing, ITCC 2000

Conference

Conference1st International Conference on Information Technology: Coding and Computing, ITCC 2000
Country/TerritoryUnited States
CityLas Vegas
Period27/03/0029/03/00

Scopus Subject Areas

  • Computer Science(all)

User-Defined Keywords

  • edge-preserving smoothing
  • image compression
  • image processing
  • model-based filter

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