Improvement of Fuzzy Image Contrast Enhancement Using Simulated Ergodic Fuzzy Markov Chains | Zendy

Behrouz Fathi-Vajargah | Zendy; Maryam Gharehdaghi | Zendy

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Improvement of Fuzzy Image Contrast Enhancement Using Simulated Ergodic Fuzzy Markov Chains

Author(s) -

Behrouz Fathi-Vajargah,

Maryam Gharehdaghi

Publication year - 2014

Publication title -

mathematical problems in engineering

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.262

H-Index - 62

eISSN - 1026-7077

pISSN - 1024-123X

DOI - 10.1155/2014/343514

Subject(s) - fuzzy logic , markov chain , ergodic theory , mathematics , image (mathematics) , contrast (vision) , image contrast , artificial intelligence , pattern recognition (psychology) , algorithm , computer science , statistics , pure mathematics

This paper presents a novel fuzzy enhancement technique using simulated ergodic fuzzy Markov chains for low contrast brain magnetic resonance imaging (MRI). The fuzzy image contrast enhancement is proposed by weighted fuzzy expected value. The membership values are then modified to enhance the image using ergodic fuzzy Markov chains. The qualitative performance of the proposed method is compared to another method in which ergodic fuzzy Markov chains are not considered. The proposed method produces better quality image

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