Regional adaptive histogram equalization using fuzzy sets

Koichi Ogawa; Atsuhisa Saito; Masato Nakajima; Yutaka Ando; Shozo Hashimoto

doi:10.1117/12.18914

1 July 1990 Regional adaptive histogram equalization using fuzzy sets

Koichi Ogawa, Atsuhisa Saito, Masato Nakajima, Yutaka Ando, Shozo Hashimoto

Proceedings Volume 1233, Medical Imaging IV: Image Processing; (1990) https://doi.org/10.1117/12.18914
Event: Medical Imaging '90, 1990, Newport Beach, CA, United States

Abstract

Contrast Limited Adaptive Histogram Equalization (CLAHE) which was developed to enhance regional contrast of an image was improved by using fuzzy sets. In the proposed method gray level transformation of each pixel is performed using each cumulative distribution function calculated from a histogram of pixel values in a contextual region of the target pixel. We optimized two parameters for making the cumulative distribution function that is size of contextual regions and a clipping level of the histogram for each pixel by using fuzzy logic. The results of simulation showed that the method not only yielded optimum contrast at any regions of an image but also reduced boundary artifacts appeared on images processed by a conventional CLAHE algorithm. 1.

Citation Download Citation

Koichi Ogawa, Atsuhisa Saito, Masato Nakajima, Yutaka Ando, and Shozo Hashimoto "Regional adaptive histogram equalization using fuzzy sets", Proc. SPIE 1233, Medical Imaging IV: Image Processing, (1 July 1990); https://doi.org/10.1117/12.18914

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