T. Do, X. Cui, Thi Hai Binh Nguyen, Hakil Kim, Van Huan Nguyen
{"title":"Blind Deconvolution Method Using Omnidirectional Gabor Filter-Based Edge Information","authors":"T. Do, X. Cui, Thi Hai Binh Nguyen, Hakil Kim, Van Huan Nguyen","doi":"10.1109/MAPR.2018.8337513","DOIUrl":null,"url":null,"abstract":"In the previous blind deconvolution methods, de- blurred images can be obtained by using the edge or pixel information. However, the existing edge- based methods did not take the advantage of edge information in ommi-directions, but only used horizontal and vertical edges when recovering the de-blurred images. This limitation lowers the quality of the recovered images. This paper proposes a method which utilizes edges in different directions to recover the true sharp image. We also provide a statistical table score to show how many directions are enough to recover a high quality true sharp image. In order to grade the quality of the deblurring image, we introduce a measurement, namely Haar defocus score that takes advantage of the Haar-Wavelet transform. The experimental results prove that the proposed method obtains a high quality deblurred image with respect to both the Haar defocus score and the Peak Signal to Noise Ratio.","PeriodicalId":349558,"journal":{"name":"2018 1st International Conference on Multimedia Analysis and Pattern Recognition (MAPR)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-04-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 1st International Conference on Multimedia Analysis and Pattern Recognition (MAPR)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MAPR.2018.8337513","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 the previous blind deconvolution methods, de- blurred images can be obtained by using the edge or pixel information. However, the existing edge- based methods did not take the advantage of edge information in ommi-directions, but only used horizontal and vertical edges when recovering the de-blurred images. This limitation lowers the quality of the recovered images. This paper proposes a method which utilizes edges in different directions to recover the true sharp image. We also provide a statistical table score to show how many directions are enough to recover a high quality true sharp image. In order to grade the quality of the deblurring image, we introduce a measurement, namely Haar defocus score that takes advantage of the Haar-Wavelet transform. The experimental results prove that the proposed method obtains a high quality deblurred image with respect to both the Haar defocus score and the Peak Signal to Noise Ratio.