λ-Enhancement: Contrast adaptation based on optimization of image fuzziness

H. R. Tizhoosh, G. Krell, B. Michaelis

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The contrast improvement of the digital images is an important task in image processing and machine vision. The gray-level modification is one of the most popular methods to perform image enhancement because it is simple in implementation and fast in computing. Since the selection of a suitable mathematical function for the gray-level transformation depends on the specific grayness properties of the image, it is necessary to develop some techniques for automatic selection of an appropriate function. In this work, we introduce a new algorithm for contrast adaptation (λ-enhancement) which is based on involutive fuzzy complements and measures of fuzziness. Regarding to the amount of grayness ambiguity the proposed technique detects the suitable form of the gray-level modification in the set of involutive membership function generated by parameter λ.

Original languageEnglish (US)
Title of host publication1998 IEEE International Conference on Fuzzy Systems Proceedings - IEEE World Congress on Computational Intelligence
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1548-1553
Number of pages6
ISBN (Print)078034863X, 9780780348639
DOIs
StatePublished - 1998
Event1998 IEEE International Conference on Fuzzy Systems, FUZZY 1998 - Anchorage, United States
Duration: May 4 1998May 9 1998

Publication series

Name1998 IEEE International Conference on Fuzzy Systems Proceedings - IEEE World Congress on Computational Intelligence
Volume2

Conference

Conference1998 IEEE International Conference on Fuzzy Systems, FUZZY 1998
Country/TerritoryUnited States
CityAnchorage
Period5/4/985/9/98

Keywords

  • fuzzy complements
  • fuzzy set theory
  • image enhancement
  • measures of fuzziness

ASJC Scopus subject areas

  • Logic
  • Control and Optimization
  • Modeling and Simulation
  • Chemical Health and Safety
  • Software
  • Safety, Risk, Reliability and Quality

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