Real-time blocking artifact reduction system based on spatially adaptive image restoration

1998 ◽  
Author(s):  
Jeongsang Lee ◽  
Yoonsik Choe
Keyword(s):  
Image Restoration ◽  
Real Time ◽  
Artifact Reduction ◽  
Reduction System ◽  
Spatially Adaptive ◽  
Blocking Artifact

Multiframe blocking-artifact reduction for transform-coded video

2002 ◽  
Vol 12 (4) ◽  
pp. 276-282 ◽  
Author(s):  
B.K. Gunturk ◽  
Y. Altunbasak ◽  
R.M. Mersereau
Keyword(s):  
Artifact Reduction ◽  
Blocking Artifact

Real-time holographic image restoration in azo dye doped polymer films

2005 ◽  
Vol 251 (4-6) ◽  
pp. 286-291 ◽  
Author(s):  
A. Yavrian ◽  
K. Asatryan ◽  
T. Galstian ◽  
M. Piché
Keyword(s):  
Image Restoration ◽  
Real Time ◽  
Polymer Films ◽  
Azo Dye ◽  
Holographic Image ◽  
Doped Polymer

An Enhanced NAS-RIF Algorithm for Blind Image Restoration Based on Total Variation Regularization

2013 ◽  
Vol 423-426 ◽  
pp. 2522-2525
Author(s):  
Xin Ke Li ◽  
Chao Gao ◽  
Yong Cai Guo ◽  
Yan Hua Shao
Keyword(s):  
Image Restoration ◽  
Total Variation ◽  
Signal To Noise Ratio ◽  
Random Noise ◽  
Tikhonov Regularization Method ◽  
Total Variation Regularization ◽  
Inverse Filtering ◽  
Blind Image Restoration ◽  
Spatially Adaptive ◽  
Blind Image

In order to improve the quality of blind image restoration, we propose an algorithm which combines Non-negativity and Support constraint Recursive Inverse Filtering (NAS-RIF) and adaptive total variation regularization. In the proposed algorithm, the total variation regularization constraint term is added in the NAS-RIF algorithm cost function. The majorization-minimization approach and conjugate gradient iterative algorithm are adopted to improve the convergence speed. We do the simulation experiments for the blurred classic test image which is added additive random noise. Experimental results show that the restoration effect of our algorithm is better than the spatially adaptive Tikhonov regularization method and the NAS-RIF spatially adaptive regularization algorithm, while the value of improvement of signal to noise ratio (ISNR) has improved.

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