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Fuzziness index driven fuzzy relaxation algorithm and applications to image processing

Author

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  • Shang-Ming Zhou
  • John Gan
  • Lida Xu
  • Robert John

Abstract

An improved fuzzy relaxation algorithm for image contrast enhancement is introduced, the relationship between the convergence regions and the parameters in the transformations defined by the algorithm is shown, which is essential to the successful application of this algorithm. Furthermore, in order to measure the quality of an enhanced image, an index of fuzziness is used in this paper to evaluate the performance of the fuzzy relaxation scheme. This extended index of fuzziness is used as a criterion for automatically stopping the fuzzy relaxation process. The analytical result is tested by experiments of image contrast enhancement. Copyright Springer Science+Business Media, LLC 2009

Suggested Citation

  • Shang-Ming Zhou & John Gan & Lida Xu & Robert John, 2009. "Fuzziness index driven fuzzy relaxation algorithm and applications to image processing," Annals of Operations Research, Springer, vol. 168(1), pages 119-131, April.
    • Handle: RePEc:spr:annopr:v:168:y:2009:i:1:p:119-131:10.1007/s10479-008-0363-9
    DOI: 10.1007/s10479-008-0363-9
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    Cited by:

    1. Ha Che-Ngoc & Thao Nguyen-Trang & Tran Nguyen-Bao & Trung Nguyen-Thoi & Tai Vo-Van, 2022. "A new approach for face detection using the maximum function of probability density functions," Annals of Operations Research, Springer, vol. 312(1), pages 99-119, May.

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