Title :
Image gray-level enhancement using Black Hole algorithm
Author :
Yaghoobi, Saber ; Hemayat, Saeed ; Mojallali, Hamed
Author_Institution :
Dept. of Electr. Eng., Univ. of Guilan, Rasht, Iran
Abstract :
Image enhancement methods are known among the most important image processing techniques. Here, image enhancement is considered as an optimization problem and a new heuristic optimization algorithm namely the Black Hole is used to solve it. Image enhancement is a nonlinear optimization problem with its particular constraints and the enhancement process will be done by intensifying each pixel´s content. In this paper, BH is employed to find the image´s optimum parameters of the transfer function in order to get the best results. BH is used here for its simplicity, ease of implementation, and also its invincibility against the parameter tuning issues. Performance of the proposed enhancement algorithm is tested against some of the well-known enhancement techniques viz. GA, PSO, HE and CS, and the obtained results indicate the robustness and also the outperformance of the proposed algorithm among its other counterparts. Enhancement in opaque images consisting of immense dominant gray values can be listed as one of the proposed method´s superiority to that of the other available in literature, which will turn the input image into an enhanced image, featuring embossed textures.
Keywords :
genetic algorithms; image enhancement; particle swarm optimisation; PSO; black hole algorithm; evolutionary optimization; heuristic optimization algorithm; image gray-level enhancement method; image processing technique; nonlinear optimization problem; opaque images; optimization; Brightness; Histograms; Image analysis; Image edge detection; Image enhancement; Optimization; Particle swarm optimization; Black Hole Algorithm; evolutionary optimization; gray-level enhancement; image processing;
Conference_Titel :
Pattern Recognition and Image Analysis (IPRIA), 2015 2nd International Conference on
Conference_Location :
Rasht
Print_ISBN :
978-1-4799-8444-2
DOI :
10.1109/PRIA.2015.7161633