{"title":"运动模糊去除与正交抛物线曝光","authors":"T. Cho, Anat Levin, F. Durand, W. Freeman","doi":"10.1109/ICCPHOT.2010.5585100","DOIUrl":null,"url":null,"abstract":"Object movement during exposure generates blur. Removing blur is challenging because one has to estimate the motion blur, which can spatially vary over the image. Even if the motion is successfully identified, blur removal can be unstable because the blur kernel attenuates high frequency image contents. We address the problem of removing blur from objects moving at constant velocities in arbitrary 2D directions. Our solution captures two images of the scene with a parabolic motion in two orthogonal directions. We show that our strategy near-optimally preserves image content, and allows for stable blur inversion. Taking two images of a scene helps us estimate spatially varying object motions. We present a prototype camera and demonstrate successful motion deblurring on real motions.","PeriodicalId":248821,"journal":{"name":"2010 IEEE International Conference on Computational Photography (ICCP)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"62","resultStr":"{\"title\":\"Motion blur removal with orthogonal parabolic exposures\",\"authors\":\"T. Cho, Anat Levin, F. Durand, W. Freeman\",\"doi\":\"10.1109/ICCPHOT.2010.5585100\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Object movement during exposure generates blur. Removing blur is challenging because one has to estimate the motion blur, which can spatially vary over the image. Even if the motion is successfully identified, blur removal can be unstable because the blur kernel attenuates high frequency image contents. We address the problem of removing blur from objects moving at constant velocities in arbitrary 2D directions. Our solution captures two images of the scene with a parabolic motion in two orthogonal directions. We show that our strategy near-optimally preserves image content, and allows for stable blur inversion. Taking two images of a scene helps us estimate spatially varying object motions. We present a prototype camera and demonstrate successful motion deblurring on real motions.\",\"PeriodicalId\":248821,\"journal\":{\"name\":\"2010 IEEE International Conference on Computational Photography (ICCP)\",\"volume\":\"27 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-03-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"62\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 IEEE International Conference on Computational Photography (ICCP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCPHOT.2010.5585100\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE International Conference on Computational Photography (ICCP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCPHOT.2010.5585100","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Motion blur removal with orthogonal parabolic exposures
Object movement during exposure generates blur. Removing blur is challenging because one has to estimate the motion blur, which can spatially vary over the image. Even if the motion is successfully identified, blur removal can be unstable because the blur kernel attenuates high frequency image contents. We address the problem of removing blur from objects moving at constant velocities in arbitrary 2D directions. Our solution captures two images of the scene with a parabolic motion in two orthogonal directions. We show that our strategy near-optimally preserves image content, and allows for stable blur inversion. Taking two images of a scene helps us estimate spatially varying object motions. We present a prototype camera and demonstrate successful motion deblurring on real motions.