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Title: Efficient blind image restoration based on 1-D generalized cross validation
Authors: Lun, DPK 
Chan, TCL
Hsung, TC
Feng, D
Issue Date: 2001
Publisher: Springer
Source: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics), 2001, v. 2195, p. 434-441 How to cite?
Journal: Lecture notes in computer science (including subseries Lecture notes in artificial intelligence and lecture notes in bioinformatics) 
Abstract: Restoring an image from its convolution with an unknown blur function is a well-known ill-posed problem in image processing. The generalized cross validation (GCV) approached was proposed to solved the problem and it has shown to have good performance in identifying the blur function and restoring the original image. However, in actual implementation, various problems incurred due to the large data sizeand long computational time of the approach are undesirable even with the current computing machines. In this paper, an efficient algorithm is proposed for blind image restoration. For this approach, the original 2-D blind image restoration problem is converted into 1-D ones by using the discrete periodic Radon transform. 1-D required are greatly reduced. Experimental results show that the resulting approach is faster in almost an order of magnitude as compared with the traditional approach, while the quality of the restored image is similar.
Description: Second IEEE Pacific Rim Conference on Multimedia, PCM 2001, Beijing, China, October 24–26, 2001
ISBN: 978-3-540-42680-6
ISSN: 0302-9743
EISSN: 1611-3349
DOI: 10.1007/3-540-45453-5_56
Appears in Collections:Conference Paper

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