{"title":"Image deblurring in super-resolution framework","authors":"Srimanta Mandal, A. Sao","doi":"10.1109/NCVPRIPG.2013.6776174","DOIUrl":null,"url":null,"abstract":"In all image processing applications, it is important to extract the appropriate information from an image. But often the captured image is not clear enough to give the required information due to the imaging environment. Thus, it is essential to enhance the clarity of the image by some post-processing techniques. Image deblurring is one of such techniques to remove the blurry effect of the captured image. This paper looks into this problem in a different way, where the deblurring of an image is addressed by solving image super-resolution problem. The blurred image is first down-sampled and then it is fed to the super-resolution framework to produce the deblurred high resolution image. In addition, the proposed approach states the requirement of edge preservation in the problem. The experimental results are comparable with the existing image deblurring algorithms.","PeriodicalId":436402,"journal":{"name":"2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG)","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 Fourth National Conference on Computer Vision, Pattern Recognition, Image Processing and Graphics (NCVPRIPG)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NCVPRIPG.2013.6776174","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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Abstract

In all image processing applications, it is important to extract the appropriate information from an image. But often the captured image is not clear enough to give the required information due to the imaging environment. Thus, it is essential to enhance the clarity of the image by some post-processing techniques. Image deblurring is one of such techniques to remove the blurry effect of the captured image. This paper looks into this problem in a different way, where the deblurring of an image is addressed by solving image super-resolution problem. The blurred image is first down-sampled and then it is fed to the super-resolution framework to produce the deblurred high resolution image. In addition, the proposed approach states the requirement of edge preservation in the problem. The experimental results are comparable with the existing image deblurring algorithms.
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超分辨率框架下的图像去模糊
在所有的图像处理应用中,从图像中提取适当的信息是很重要的。但由于成像环境的原因,通常捕获的图像不够清晰,无法提供所需的信息。因此,通过一些后处理技术来增强图像的清晰度是很有必要的。图像去模糊是一种消除所捕获图像模糊效果的技术。本文从另一个角度来研究这一问题,即通过解决图像超分辨率问题来解决图像的去模糊问题。首先对模糊图像进行下采样,然后将其送入超分辨率框架,产生去模糊的高分辨率图像。此外,该方法还说明了问题中边缘保持的要求。实验结果与现有图像去模糊算法具有可比性。
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