{"title":"A customized Particle Swarm Optimization algorithm for image enhancement","authors":"K. Venkatalakshmi, S. Shalinie","doi":"10.1109/ICCCCT.2010.5670768","DOIUrl":null,"url":null,"abstract":"Particle Swarm Optimization (PSO) modified to solve image processing problem with reference to enhancement technique is proposed in this paper. The enhancement process is an optimization problem with several constraints. The objective of the proposed PSO is to maximize an objective fitness criterion in order to improve the contrast and detail in an image by adapting the parameters of a novel extension to a local enhancement technique. The feasibility of the proposed method is demonstrated and compared with the standard versions of the PSO based image enhancement technique presented in the literature. The obtained results indicate that the proposed PSO yields better results in terms of the maximization of the number of pixels in the edges and the computational time.","PeriodicalId":250834,"journal":{"name":"2010 INTERNATIONAL CONFERENCE ON COMMUNICATION CONTROL AND COMPUTING TECHNOLOGIES","volume":"303 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-12-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"12","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 INTERNATIONAL CONFERENCE ON COMMUNICATION CONTROL AND COMPUTING TECHNOLOGIES","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCCCT.2010.5670768","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 12
Abstract
Particle Swarm Optimization (PSO) modified to solve image processing problem with reference to enhancement technique is proposed in this paper. The enhancement process is an optimization problem with several constraints. The objective of the proposed PSO is to maximize an objective fitness criterion in order to improve the contrast and detail in an image by adapting the parameters of a novel extension to a local enhancement technique. The feasibility of the proposed method is demonstrated and compared with the standard versions of the PSO based image enhancement technique presented in the literature. The obtained results indicate that the proposed PSO yields better results in terms of the maximization of the number of pixels in the edges and the computational time.