Title :
An automated GA-based fuzzy image enhancement method
Author :
Khayat, Omid ; Razjouyan, Javad ; Aghvami, Mina ; Shahdoosti, Hamid Reza ; Loni, Babak
fDate :
March 30 2009-April 2 2009
Abstract :
This paper presents an automated algorithm for image enhancement. A novel parametric indices of fuzziness (PIF) is introduced, which serves as the optimization criterion of the contrast enhancement procedure. The proposed PIF comprises the Sugeno class of involutive fuzzy complements and the first order fuzzy moment of the image. The PIF as the measure of fuzziness should be maximized, and the maximum of PIF is tuned based on the first-order fuzzy moment of the image. The parameters of the transformation function are found by the genetic algorithm aiming to maximize the PIF. Finally, several experiments are made to demonstrate the efficiency of the proposed method.
Keywords :
fuzzy set theory; genetic algorithms; image enhancement; Sugeno class; first-order fuzzy moment; genetic algorithm; image enhancement; parametric indices of fuzziness; transformation function; Image enhancement; Fuzzy complements; Genetic algorithm; Image enhancement; Measure of fuzziness; Parametric indices of fuzziness;
Conference_Titel :
Computational Intelligence for Image Processing, 2009. CIIP '09. IEEE Symposium on
Conference_Location :
Nashville, TN
Print_ISBN :
978-1-4244-2760-4
DOI :
10.1109/CIIP.2009.4937874