Open AccessImage enhancement based on intuitionistic fuzzy sets theory
Author(s) -
Deng He,
Sun Xianping,
Liu Maili,
Ye Chaohui,
Zhou Xin
Publication year - 2016
Publication title -
iet image processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.401
H-Index - 45
eISSN - 1751-9667
pISSN - 1751-9659
DOI - 10.1049/iet-ipr.2016.0035
Subject(s) - fuzzy set , artificial intelligence , computer science , fuzzy logic , image (mathematics) , object (grammar) , image enhancement , defuzzification , pattern recognition (psychology) , computer vision , image quality , mathematics , fuzzy number
Enhancement of images with weak edges faces great challenges in imaging applications. In this study, the authors propose a novel image enhancement approach based on intuitionistic fuzzy sets. The proposed method first divides an image into sub‐object and sub‐background areas, and then successively implements new fuzzification, hyperbolisation, and defuzzification operations on each area. In this way, an enhanced image is obtained, where the visual quality of region of interest (ROI) is significantly improved. Several types of images are utilised to validate the proposed method with respect to the enhancement performance. Experimental results demonstrate that the proposed algorithm not only works more stably for different types of images, but also has better enhancement performance, in comparison to conventional methods. This is a great merit of such design for discerning specific ROIs.