{"title":"Joint video fusion and super resolution based on Markov random fields","authors":"Jin Chen, J. Núñez-Yáñez, A. Achim","doi":"10.1109/ICIP.2014.7025431","DOIUrl":null,"url":null,"abstract":"In this paper, a joint video fusion and super-resolution algorithm is proposed. The method addresses the problem of generating a high-resolution (HR) image from infrared (IR) and visible (VI) low-resolution (LR) images, in a Bayesian framework. In order to preserve better the discontinuities, a Generalized Gaussian Markov Random Field (MRF) is used to formulate the prior. Experimental results demonstrate that information from both visible and infrared bands is recovered from the LR frames in an effective way.","PeriodicalId":6856,"journal":{"name":"2014 IEEE International Conference on Image Processing (ICIP)","volume":"130 1","pages":"2150-2154"},"PeriodicalIF":0.0000,"publicationDate":"2014-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE International Conference on Image Processing (ICIP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICIP.2014.7025431","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
In this paper, a joint video fusion and super-resolution algorithm is proposed. The method addresses the problem of generating a high-resolution (HR) image from infrared (IR) and visible (VI) low-resolution (LR) images, in a Bayesian framework. In order to preserve better the discontinuities, a Generalized Gaussian Markov Random Field (MRF) is used to formulate the prior. Experimental results demonstrate that information from both visible and infrared bands is recovered from the LR frames in an effective way.
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