NDLI: Motion deblurring as optimisation

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Motion deblurring as optimisation

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Motion deblurring as optimisation

Content Provider	ACM Digital Library
Author	Veeravasarapu, V. S. Rao Sivaswamy, Jayanthi
Abstract	Motion blur is one of the most common causes of image degradation. It is of increasing interest due to the deep penetration of digital cameras into consumer applications. In this paper, we start with a hypothesis that there is sufficient information within a blurred image and approach the deblurring problem as an optimisation process where the deblurring is to be done by satisfying a set of conditions. These conditions are derived from first principles underlying the degradation process assuming noise-free environments. We propose a novel but effective method for removing motion blur from a single blurred image via an iterative algorithm. The strength of this method is that it enables deblurring without resorting to estimation of the blur kernel or blur depth. The proposed iterative method has been tested on several images with different degrees of blur. The obtained results have been compared with state of the art techniques including those that require more than one input image. The results are consistently of high quality and comparable or superior to the existing methods which demonstrates the effectiveness of the proposed technique.
Starting Page	267
Ending Page	273
Page Count	7
File Format	PDF
ISBN	9781450300605
DOI	10.1145/1924559.1924595
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2010-12-12
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Burg's entropy De-blurring Motion blurred image Shannon's entropy Univariate optimization
Content Type	Text
Resource Type	Article

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