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A New Fuzzy Rule Based Contrast Enhancement Method using The Two-Steps Automatic Clustering Algorithm

Ha Che-Ngoc, Anh-Thy Pham-Chau, Dibya Jyoti Bora

Journal of Advanced Engineering and Computation · 2018

doi:10.25073/jaec.201824.214 (opens in a new tab)

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Abstract

The contrast is a major factor influencing the image quality; therefore, image contrast enhancement technique is more and more widely applied in the field of image processing. In this paper, a new fuzzy rule-based contrast enhancement method using the two-steps automatic clustering algorithm is proposed. Specifically, based on the Automatic clustering algorithm, a state-of-art method in cluster analysis and data mining, this paper proposes a two-steps Automatic clustering method to determine the number of fuzzy sets and locate the critical point in membership functions so that they are suitable for the distribution of pixel intensity values. The experiments on the "Lena" image and other natural images demonstrate that the new method can effectively enhance the contrast of the images and meet the demands of human eyes perception at the same time.This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium provided the original work is properly cited.

Abstract licence: CC BY

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