Watershed-based maximum-homogeneity filtering

Michael W. Hansen, William Evan Higgins

Research output: Contribution to journalArticle

8 Citations (Scopus)

Abstract

We introduce an image enhancement method referred to as the watershed-based maximum-homogeneity filter. This method first uses watershed analysis to subdivide the image into homogeneous pixel clusters called catchment basins. Next, using an adaptive, local, catchment-basin selection scheme, similar neighboring catchment basins are combined together to produce an enhanced image. Because the method starts with watershed analysis, it can preserve edge information and run with high computational efficiency. Illustrative results show that the method performs well relative to other popular nonlinear filters.

Original languageEnglish (US)
Pages (from-to)982-988
Number of pages7
JournalIEEE Transactions on Image Processing
Volume8
Issue number7
DOIs
StatePublished - Jan 1 1999

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Watersheds
Catchments
Image Enhancement
Image enhancement
Computational efficiency
Pixels

All Science Journal Classification (ASJC) codes

  • Software
  • Medicine(all)
  • Computer Graphics and Computer-Aided Design

Cite this

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Watershed-based maximum-homogeneity filtering. / Hansen, Michael W.; Higgins, William Evan.

In: IEEE Transactions on Image Processing, Vol. 8, No. 7, 01.01.1999, p. 982-988.

Research output: Contribution to journalArticle

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