Open AccessNatural Image Enhancement Using a Biogeography Based Optimization Enhanced with Blended Migration Operator
Author(s) -
J. Jasper,
S. Berlin Shaheema,
S. Berlin Shiny
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 - 10.1155/2014/232796
Subject(s) - image (mathematics) , operator (biology) , computer science , entropy (arrow of time) , enhanced data rates for gsm evolution , image processing , image enhancement , artificial intelligence , optimization algorithm , computer vision , mathematical optimization , mathematics , biochemistry , chemistry , physics , repressor , quantum mechanics , transcription factor , gene
This paper addresses a novel and efficient algorithm for solving optimization problem in image processing applications. Image enhancement (IE) is one of the complex optimization problems in image processing. The main goal of this paper is to enhance color images such that the eminence of the image is more suitable than the original image from the perceptual viewpoint of human. Traditional methods require prior knowledge of the image to be enhanced, whereas the aim of the proposed biogeography based optimization (BBO) enhanced with blended migration operator (BMO) algorithm is to maximize the objective function in order to enhance the image contrast by maximizing the parameters like edge intensity, edge information, and entropy. Experimental results are compared with the current state-of-the-art approaches and indicate the superiority of the proposed technique in terms of subjective and objective evaluation
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