A study on moving image noise removal using 3D and time-domain total variation regularization method

2019 ◽  
Author(s):  
Tsubasa Munezawa ◽  
Tomio Goto ◽  
Satoshi Hirano ◽  
Son L. Phung
Keyword(s):  
Total Variation ◽  
Time Domain ◽  
Regularization Method ◽  
Noise Removal ◽  
Image Noise ◽  
Total Variation Regularization ◽  
Moving Image

scholarly journals Image noise removal based on total variation

2015 ◽  
Vol 39 (4) ◽  
pp. 564-571 ◽  
Author(s):  
D.N.H. Thanh ◽  
◽  
S.D. Dvoenko ◽  
Keyword(s):  
Total Variation ◽  
Noise Removal ◽  
Image Noise

scholarly journals Multidirectional Anisotropic Total Variation and Its Application in the Tomography of the Surrounding Rock of Coal Mining Faces

2021 ◽  
Vol 2021 ◽  
pp. 1-15
Author(s):  
Bo Chen ◽  
Guowei Zhu ◽  
Zhenqiang Yang
Keyword(s):  
Coal Mining ◽  
Total Variation ◽  
Regularization Method ◽  
Surrounding Rock ◽  
Total Variation Regularization ◽  
Ct Reconstruction ◽  
Traveltime Tomography ◽  
Transmitted Waves ◽  
Mining Face ◽  
Anisotropic Total Variation

The computed tomography (CT) reconstruction algorithm is one of the crucial components of the CT system. To date, total variation (TV) has been widely used in CT reconstruction algorithms. Although TV utilizes the a priori information of the longitudinal and lateral gradient sparsity of an image, it introduces some staircase artifacts. To overcome the current limitations of TV and improve imaging quality, we propose a multidirectional anisotropic total variation (MATV) that uses multidirectional gradient information. The surrounding rock of coal mining faces uses principles of tomography similar to those of medical X-rays. The velocity distribution for the surrounding rock can be obtained by the first-arrival traveltime tomography of the transmitted waves in the coal mining face. Combined with the geological data, we can interpret the geological hazards in the coal mining face. To perform traveltime tomography, we first established the objective function of the first-arrival traveltime tomography of the transmitted waves based on the MATV regularization and then used the split Bregman method to solve the objective function. The simulated data and real data show that the MATV regularization method proposed in this paper can better maintain the boundaries of geological anomalies and reduce the artifacts compared with the isotropic total variation regularization method and the anisotropic total variation regularization method. Furthermore, this approach describes the distribution of geological anomalies more accurately and effectively and improves imaging accuracy.

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