Statistics-Guided Residual Dictionary Learning for Footprint Noise Removal

Author(s):  
Wei Chen ◽  
Omar M. Saad ◽  
Hang Wang ◽  
Yangkang Chen
2013 ◽  
Vol 93 (9) ◽  
pp. 2696-2708 ◽  
Author(s):  
Shanshan Wang ◽  
Qiegen Liu ◽  
Yong Xia ◽  
Pei Dong ◽  
Jianhua Luo ◽  
...  

Algorithms ◽  
2018 ◽  
Vol 12 (1) ◽  
pp. 7
Author(s):  
Di Guo ◽  
Zhangren Tu ◽  
Jiechao Wang ◽  
Min Xiao ◽  
Xiaofeng Du ◽  
...  

Images may be corrupted by salt and pepper impulse noise during image acquisitions or transmissions. Although promising denoising performances have been recently obtained with sparse representations, how to restore high-quality images remains challenging and open. In this work, image sparsity is enhanced with a fast multiclass dictionary learning, and then both the sparsity regularization and robust data fidelity are formulated as minimizations of L0-L0 norms for salt and pepper impulse noise removal. Additionally, a numerical algorithm of modified alternating direction minimization is derived to solve the proposed denoising model. Experimental results demonstrate that the proposed method outperforms the compared state-of-the-art ones on preserving image details and achieving higher objective evaluation criteria.


2020 ◽  
Vol 11 (2) ◽  
pp. 586
Author(s):  
Mahad Esmaeili ◽  
Alireza Mehri Dehnavi ◽  
Fedra Hajizadeh ◽  
Hossein Rabbani

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