{"title":"A no-reference blur metric guided fusion technique for multi-focus images","authors":"Ramy M. Bahy, G. Salama, T. Mahmoud","doi":"10.1109/NRSC.2011.5873620","DOIUrl":null,"url":null,"abstract":"This paper presents a new partition fusion technique for multi-focus images based on a no-reference blur metric. The no-reference blur metric is used to evaluate the amount of blur in images whereby, in many practical applications the original images are not available. The proposed algorithm is considered as a region based fusion technique, in which each of the input images are divided into a set of blocks and then the no-reference blur metric is used to evaluate the amount of blur in each block. Finally the less blurred block (sub-image) is selected as a part of the output fused image. In this paper the input images are considered registered whereas; our paper put a focus on image fusion field. The proposed technique considers the presence of overlapped blurred regions in input images; however previous related works didn't consider this assumption. Experimental results show that image fusion based on the selected no-reference blur metric give better performance against other algorithms based on traditional blur measurements.","PeriodicalId":438638,"journal":{"name":"2011 28th National Radio Science Conference (NRSC)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2011-04-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 28th National Radio Science Conference (NRSC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NRSC.2011.5873620","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 7
Abstract
This paper presents a new partition fusion technique for multi-focus images based on a no-reference blur metric. The no-reference blur metric is used to evaluate the amount of blur in images whereby, in many practical applications the original images are not available. The proposed algorithm is considered as a region based fusion technique, in which each of the input images are divided into a set of blocks and then the no-reference blur metric is used to evaluate the amount of blur in each block. Finally the less blurred block (sub-image) is selected as a part of the output fused image. In this paper the input images are considered registered whereas; our paper put a focus on image fusion field. The proposed technique considers the presence of overlapped blurred regions in input images; however previous related works didn't consider this assumption. Experimental results show that image fusion based on the selected no-reference blur metric give better performance against other algorithms based on traditional blur measurements.