| Removing Atmospheric Turbulence via Space-Invariant Deconvolution. | |
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MedLine Citation:
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PMID: 23154324 Owner: NLM Status: In-Data-Review |
Abstract/OtherAbstract:
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To correct geometric distortion and reduce space and time-varying blur, a new approach is proposed in this paper capable of restoring a single high-quality image from a given image sequence distorted by atmospheric turbulence. This approach reduces the space and time-varying deblurring problem to a shift invariant one. It first registers each frame to suppress geometric deformation through B-spline-based nonrigid registration. Next, a temporal regression process is carried out to produce an image from the registered frames, which can be viewed as being convolved with a space invariant near-diffraction-limited blur. Finally, a blind deconvolution algorithm is implemented to deblur the fused image, generating a final output. Experiments using real data illustrate that this approach can effectively alleviate blur and distortions, recover details of the scene, and significantly improve visual quality. |
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Authors:
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Xiang Zhu; Peyman Milanfar |
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Publication Detail:
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Type: Journal Article |
Journal Detail:
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Title: IEEE transactions on pattern analysis and machine intelligence Volume: 35 ISSN: 1939-3539 ISO Abbreviation: IEEE Trans Pattern Anal Mach Intell Publication Date: 2013 Jan |
Date Detail:
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Created Date: 2012-11-16 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 9885960 Medline TA: IEEE Trans Pattern Anal Mach Intell Country: United States |
Other Details:
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Languages: eng Pagination: 157-70 Citation Subset: IM |
Affiliation:
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University of California, Santa Cruz, Santa Cruz. |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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