Sparsity constrained regularization for multiframe image restoration
JOSA A, Vol. 25, Issue 5, pp. 1199-1214 (2008)
http://dx.doi.org/10.1364/JOSAA.25.001199
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Abstract
In this paper we present a new algorithm for restoring an object from multiple undersampled low-resolution (LR) images that are degraded by optical blur and additive white Gaussian noise. We formulate the multiframe superresolution problem as maximum a posteriori estimation. The prior knowledge that the object is sparse in some domain is incorporated in two ways: first we use the popular
© 2008 Optical Society of America
OCIS Codes
(100.6640) Image processing : Superresolution
(110.4155) Imaging systems : Multiframe image processing
ToC Category:
Image Processing
History
Original Manuscript: November 29, 2007
Manuscript Accepted: February 21, 2008
Published: April 30, 2008
Citation
Premchandra M. Shankar and Mark A. Neifeld, "Sparsity constrained regularization for multiframe image restoration," J. Opt. Soc. Am. A 25, 1199-1214 (2008)
http://www.opticsinfobase.org/josaa/abstract.cfm?URI=josaa-25-5-1199
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