{"title":"Temporal resolution enhancement of image sequences capturing evolving weather phenomena","authors":"I. Yanovsky, B. Lambrigtsen","doi":"10.1109/MICRORAD.2016.7530525","DOIUrl":null,"url":null,"abstract":"In this paper, we develop an approach for temporal resolution enhancement of blurry and distorted image sequences capturing evolving weather phenomena. We first enhance the spatial resolution of a sequence of images using an efficient deconvolution method which we showed to reduce image ringing, blurring, and distortion, while sharpening the image and preserving information content. Such methodology is based on current research in sparse optimization and compressed sensing, which lead to unprecedented efficiencies for solving image reconstruction problems. We then consider the evolving sequence to be embedded in a deformable medium, and enhance temporal resolution of a sequence using nonlinear viscous fluid registration model. The physical continuum equation is solved using an efficient multigrid full approximation scheme.","PeriodicalId":330696,"journal":{"name":"2016 14th Specialist Meeting on Microwave Radiometry and Remote Sensing of the Environment (MicroRad)","volume":"73 3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-04-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 14th Specialist Meeting on Microwave Radiometry and Remote Sensing of the Environment (MicroRad)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MICRORAD.2016.7530525","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
In this paper, we develop an approach for temporal resolution enhancement of blurry and distorted image sequences capturing evolving weather phenomena. We first enhance the spatial resolution of a sequence of images using an efficient deconvolution method which we showed to reduce image ringing, blurring, and distortion, while sharpening the image and preserving information content. Such methodology is based on current research in sparse optimization and compressed sensing, which lead to unprecedented efficiencies for solving image reconstruction problems. We then consider the evolving sequence to be embedded in a deformable medium, and enhance temporal resolution of a sequence using nonlinear viscous fluid registration model. The physical continuum equation is solved using an efficient multigrid full approximation scheme.