Non-local/local image filters using fast eigenvalue filtering

Author(s):  
Masaki Onuki ◽  
Shunsuke Ono ◽  
Keiichiro Shirai ◽  
Yuichi Tanaka
Keyword(s):  
2009 ◽  
pp. 943-949
Author(s):  
Abdenour Hadid ◽  
Matti Pietikäinen
Keyword(s):  

2014 ◽  
Vol 34 (6) ◽  
pp. 111-122 ◽  
Author(s):  
Wei Li ◽  
Lei Zhao ◽  
Zhijie Lin ◽  
Duanqing Xu ◽  
Dongming Lu

2013 ◽  
Vol 411-414 ◽  
pp. 1164-1169 ◽  
Author(s):  
Zhi Ming Wang ◽  
Hong Bao

Image deblurring with noise is a typical ill-posed problem needs regularization. Various regularization models were proposed during several decades study, such as Tikhonov and TV. A new regularization model based non-local similarity constrains is proposed in this paper, which used l2 non-local norms and could be easily solved by fast non-local image denoising algorithm. By combining with Bregmanrized operator splitting (BOS) algorithm, a fast and efficient iterative three step image deblurring scheme is given. Experimental results show that proposed regularization model obtained better results on ten common test images than other similar regularization model including newly proposed NLTV regularization, both in deblurring performance (PSNR and MSSIM) and processing speed.


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