A fuzzy-based contrast enhancement for high resolution satellite images

Chi Farn Chen, Hung Yu Chang, Li Yu Chang

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

1 Scopus citations

Abstract

Many conventional contrast enhancement techniques adopt a global approach to enhance the image. However, it is usually difficult to enhance all land cover classes appearing in the satellite image using these approaches, because local contrast information and details may be lost in the dark and bright areas. In this study, a three-stage algorithm based on fuzzy set theory is proposed to deal with the problem. First, the satellite image is transformed from gray-level space to membership space by fuzzy c-means clustering. Second, appropriate stretch model of each class is individually constructed based on corresponding memberships. Third, the image is transformed back to the gray-level space by merging stretched gray values of each class. Finally, the performance of the proposed scheme is evaluated qualitatively and quantitatively. The results show that the proposed method can successfully enhance satellite images and provide better contrast images for visual interpretation and visualization.

Original languageEnglish
Title of host publication28th Asian Conference on Remote Sensing 2007, ACRS 2007
Pages2105-2110
Number of pages6
StatePublished - 2007
Event28th Asian Conference on Remote Sensing 2007, ACRS 2007 - Kuala Lumpur, Malaysia
Duration: 12 Nov 200716 Nov 2007

Publication series

Name28th Asian Conference on Remote Sensing 2007, ACRS 2007
Volume3

Conference

Conference28th Asian Conference on Remote Sensing 2007, ACRS 2007
Country/TerritoryMalaysia
CityKuala Lumpur
Period12/11/0716/11/07

Keywords

  • Contrast enhancement
  • Fuzzy C-means
  • Fuzzy set
  • Satellite image

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