The Role of Entropy in Intuitionistic Fuzzy Contrast Enhancement

Author(s):  
Ioannis K. Vlachos ◽  
George D. Sergiadis
1998 ◽  
Vol 38 (6) ◽  
pp. 783-787 ◽  
Author(s):  
Robert F. Hess ◽  
Steven C. Dakin ◽  
David J. Field
Keyword(s):  

Author(s):  
Daniel M. Wonohadidjojo

The article presented the enhancement method of cells images. The first method used in the local contrast enhancement was Intuitionistic Fuzzy Sets (IFS). The proposed method is the IFS optimized by Artificial Bee Colony (ABC) algorithm. The ABC was used to optimize the membership function parameter of IFS. To measure the image quality, Image Enhancement Metric (IEM)was applied. The results of local contrast enhancement using both methods were compared with the results using histogram equalization method. The tests were conducted using two MDCK cell images. The results of local contrast enhancement using both methods were evaluated by observing the enhanced images and IEM values. The results show that the methods outperform the histogram equalization method. Furthermore, the method using IFSABC is better than the IFS method.


2019 ◽  
Vol 25 (3) ◽  
pp. 54
Author(s):  
M. V. Andreevskaya ◽  
M. R. Kabardieva ◽  
A. E. Komlev ◽  
T. É. Imaev ◽  
V. G. Naumov ◽  
...  

2019 ◽  
Vol 8 (1) ◽  
pp. 65-82
Author(s):  
Payel Ghosh ◽  
Tapan Kumar Roy

The objective of this article is to tie a knot between distance measure and fuzzy and intuitionistic fuzzy optimization through goal programming. Firstly, a distance measure for an intuitionistic fuzzy number is developed, and then it is implemented into an intuitionistic fuzzy nonlinear goal programming. Then using some conditions, the distance measure of intuitionistic fuzzy number is converted into distance measure of fuzzy number and a comparative study using a numerical example is shown for highest applicability of distance measure based intuitionistic fuzzy goal programming than distance measure based fuzzy goal programming.


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