Survey on Blind Image Deblurring Using Row-Column Sparse Representations
Volume: 7 - Issue: 04 - Date: 01-04-2018
Approved ISSN: 2278-1412
Published Id: IJAECESTU346 | Page No.: 101-104
Author: Manish Patel
Co- Author: Prof. Meha Shrivastava,Prof. Ankita Jain
Abstract:-This paper presents different method for blind image deblurring. The method only
makes weak assumptions about the blurring filter and is able to undo a wide variety of blurring
degradations. The use of constrained blur models appropriate to the problem at hand, and/or of
multiframe scenarios, generally improves the deblurring results. Tests performed on monochrome
and color images, with various synthetic and real-life degradations, without and with noise, in
single-frame and multiframe scenarios, showed good analysis, both in subjective terms and in
terms of the increase of signal to noise ratio (ISNR) measure. In comparisons with other state of
the art methods, our method yields better results, and shows to be applicable to a much wider
range of blurs. To overcome the ill-posedness of the blind image deblurring problem, the method
includes a learning technique which initially focuses on the main edges of the image and gradually
takes details into account. A new image prior, which includes a new edge detector, is used.
Key Words:-Deblurring, SNR, DWT
Area:-Engineering
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