{"title":"Mapping of visible to IR data for scene matching","authors":"M. A. Chaudhry, A. Baig, R. Nawaz","doi":"10.1109/IBCAST.2012.6177526","DOIUrl":null,"url":null,"abstract":"Scene matching has become a challenging problem due to multi-temporal and multi-modal image acquisition. There is no direct and linear relation between EO (Electro-optical) and IR (Infra-red) images, which are required to be matched. In this paper, we propose a statistical technique of mapping EO to IR data by transformation function deduced from their gray level distribution. As the proposed technique is statistical and deals with multi-modal data, MI index (Mutual Information) and its variants are more appropriate similarity measures in this case. Therefore, we have used mutual information as a measure of statistical dependence between the two images. Results of MI shows that technique is effective in mapping visible to IR spectrum.","PeriodicalId":251584,"journal":{"name":"Proceedings of 2012 9th International Bhurban Conference on Applied Sciences & Technology (IBCAST)","volume":"72 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 2012 9th International Bhurban Conference on Applied Sciences & Technology (IBCAST)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IBCAST.2012.6177526","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Scene matching has become a challenging problem due to multi-temporal and multi-modal image acquisition. There is no direct and linear relation between EO (Electro-optical) and IR (Infra-red) images, which are required to be matched. In this paper, we propose a statistical technique of mapping EO to IR data by transformation function deduced from their gray level distribution. As the proposed technique is statistical and deals with multi-modal data, MI index (Mutual Information) and its variants are more appropriate similarity measures in this case. Therefore, we have used mutual information as a measure of statistical dependence between the two images. Results of MI shows that technique is effective in mapping visible to IR spectrum.