Non-blind image deconvolution using natural image gradient prior

Since non-blind image deconvolution is inherently ill-posed, the results of unregularized methods are often contaminated by noise and ringing artifacts. To reach a stable solution, we adopt the natural image gradient prior to regularize the latent image and obtain an improved version of the Richards...

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Bibliographic Details
Published inOptik (Stuttgart) Vol. 124; no. 24; pp. 6599 - 6605
Main Authors Tao, Shuyin, Dong, Wende, Feng, Huajun, Xu, Zhihai, Li, Qi
Format Journal Article
LanguageEnglish
Published Elsevier GmbH 01.12.2013
Subjects
Algorithms
Blurred
Contamination
Deconvolution
Image quality
Natural image gradient prior
Noise
Non-blind image deconvolution
Regularization
Richardson–Lucy (RL) algorithm
Non-blind image deconvolution
Regularization
Natural image gradient prior
Richardson–Lucy (RL) algorithm
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Summary:Since non-blind image deconvolution is inherently ill-posed, the results of unregularized methods are often contaminated by noise and ringing artifacts. To reach a stable solution, we adopt the natural image gradient prior to regularize the latent image and obtain an improved version of the Richardson–Lucy (RL) algorithm. We use both synthetic and real world blurred images to test the proposed method. Experimental results show that the negative artifacts are significantly suppressed and the restored images are of high quality.
Bibliography:ObjectType-Article-2
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content type line 23
ISSN:0030-4026
1618-1336
DOI:10.1016/j.ijleo.2013.05.068