Curvelet Shrinkage Based Iterative Regularization Method for Image Denoising

Author(s):  
Min Li ◽  
Xiaoli Sun
2017 ◽  
Vol 396 ◽  
pp. 108-121 ◽  
Author(s):  
Zhifei Zhang ◽  
Si Chen ◽  
Zhongming Xu ◽  
Yansong He ◽  
Shu Li

2016 ◽  
Vol 26 (3) ◽  
pp. 623-640 ◽  
Author(s):  
Sara Beddiaf ◽  
Laurent Autrique ◽  
Laetitia Perez ◽  
Jean-Claude Jolly

Abstract Inverse three-dimensional heat conduction problems devoted to heating source localization are ill posed. Identification can be performed using an iterative regularization method based on the conjugate gradient algorithm. Such a method is usually implemented off-line, taking into account observations (temperature measurements, for example). However, in a practical context, if the source has to be located as fast as possible (e.g., for diagnosis), the observation horizon has to be reduced. To this end, several configurations are detailed and effects of noisy observations are investigated.


2009 ◽  
Vol 36 (10) ◽  
pp. 2548-2551
Author(s):  
陈冠楠 Chen Guannan ◽  
陈荣 Chen Rong ◽  
林居强 Lin Juqiang ◽  
黄祖芳 Huang Zufang ◽  
冯尚源 Feng Shangyuan ◽  
...  

2014 ◽  
Vol 2014 ◽  
pp. 1-9
Author(s):  
Hao Cheng ◽  
Ping Zhu ◽  
Jie Gao

A regularization method for solving the Cauchy problem of the Helmholtz equation is proposed. Thea priorianda posteriorirules for choosing regularization parameters with corresponding error estimates between the exact solution and its approximation are also given. The numerical example shows the effectiveness of this method.


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