Deblurring by Matching.

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Bibliographic Details
Title:	Deblurring by Matching.
Authors:	Ancuti, Cosmin¹ cosmin.ancuti@uhasselt.be, Ancuti, Codruta Orniana¹ codruta.ancuti@uhasselt.be, Bekaert, Philippe¹ philippe.bekaert@uhasselt.be
Source:	Computer Graphics Forum. Apr2009, Vol. 28 Issue 2, p619-628. 10p. 8 Color Photographs.
Subjects:	Digital image processing software, Digital photography software, Computer vision, Deconvolution (Mathematics), Spectrum analysis, Computer software, Preservation of photographs, Computer graphics software
Abstract:	Restoration of the photographs damaged by the camera shake is a challenging task that manifested increasing attention in the recent period. Despite of the important progress of the blind deconvolution techniques, due to the ill-posed nature of the problem, the finest details of the kernel blur cannot be recovered entirely. Moreover, the additional constraints and prior assumptions make these approaches to be relative limited. In this paper we introduce a novel technique that removes the undesired blur artifacts from photographs taken by hand-held digital cameras. Our approach is based on the observation that in general several consecutive photographs taken by the users share image regions that project the same scene content. Therefore, we took advantage of additional sharp photographs of the same scene. Based on several invariant local feature points, filtered from the given blurred/non-blurred images, our approach matches the keypoints and estimates the blur kernel using additional statistical constraints. We also present a simple deconvolution technique that preserves edges while minimizing the ringing artifacts in the restored latent image. The experimental results prove that our technique is able to infer accurately the blur kernel while reducing significantly the artifacts of the spoilt images. [ABSTRACT FROM AUTHOR]
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Database:	Engineering Source

Description
Abstract:	Restoration of the photographs damaged by the camera shake is a challenging task that manifested increasing attention in the recent period. Despite of the important progress of the blind deconvolution techniques, due to the ill-posed nature of the problem, the finest details of the kernel blur cannot be recovered entirely. Moreover, the additional constraints and prior assumptions make these approaches to be relative limited. In this paper we introduce a novel technique that removes the undesired blur artifacts from photographs taken by hand-held digital cameras. Our approach is based on the observation that in general several consecutive photographs taken by the users share image regions that project the same scene content. Therefore, we took advantage of additional sharp photographs of the same scene. Based on several invariant local feature points, filtered from the given blurred/non-blurred images, our approach matches the keypoints and estimates the blur kernel using additional statistical constraints. We also present a simple deconvolution technique that preserves edges while minimizing the ringing artifacts in the restored latent image. The experimental results prove that our technique is able to infer accurately the blur kernel while reducing significantly the artifacts of the spoilt images. [ABSTRACT FROM AUTHOR]
ISSN:	01677055
DOI:	10.1111/j.1467-8659.2009.01402.x