A novel weighted anisotropic total variational model for image applications

2021 ◽  
Author(s):  
Meng-Meng Li ◽  
Bing-Zhao Li
Keyword(s):  
Variational Model ◽  
Total Variational Model

scholarly journals A non-local vectorial total variational model for multichannel SAR image speckle suppression

2015 ◽  
Vol 28 (3) ◽  
pp. 770-779 ◽  
Author(s):  
Rubing Xi ◽  
Zhengming Wang ◽  
Meihua Xie ◽  
Xia Zhao ◽  
Weiwei Wang
Keyword(s):  
Variational Model ◽  
Sar Image ◽  
Non Local ◽  
Total Variational Model ◽  
Speckle Suppression

A New Denoising Approach for Optical Coherence Tomography Image Based on the Total Variational Model

2013 ◽  
Vol 278-280 ◽  
pp. 1383-1387
Author(s):  
Jing Liu ◽  
Xiao Lin Tian ◽  
Yan Kui Sun
Keyword(s):  
Variational Model ◽  
Optical Coherence Tomography Image ◽  
The Novel ◽  
Signal Noise ◽  
Noise Image ◽  
Tomography Image ◽  
Noise Ratio ◽  
Image Details ◽  
Total Variational Model ◽  
Tv Model

The traditional total variational (TV) model performs well for most noise image. However, the method will lose some information and details for the image which has rich texture and tiny boundary. Therefore, according to the requirements of the OCT pearl image, a novel denoising approach based on the TV model is proposed in this paper. This method combined the adaptive image denoising model and the novel fidelity term. Numerical experiments show that the proposed method can remove the noise while preserving significant image details. At pearl OCT image the method achieves at least 0.1dB gain over other existing denoising methods for Signal-Noise Ratio (SNR) measurement and Peak Signal-Noise Ratio (PSNR) measurement.

scholarly journals Dark Channel Constraint and Alternated Direction Multiplier Optimization of Turbulence Degraded Image Blind Restoration

2018 ◽  
Vol 36 (1) ◽  
pp. 103-109
Author(s):  
Huihui Li ◽  
Lun Yu ◽  
Liang Zhang ◽  
Ning Yang
Keyword(s):  
Image Restoration ◽  
Prior Information ◽  
Descent Method ◽  
Variational Model ◽  
Posteriori Probability ◽  
A Posteriori Probability ◽  
Dark Channel ◽  
Degraded Image ◽  
Blind Restoration ◽  
Total Variational Model

In order to improve the effect of turbulence degraded image restoration, aiming at the problem that the fuzzy solution is easy to be obtained by using the prior information constraint of gradient distribution under the framework of maximum a posteriori probability of blind restoration algorithm, this paper proposes a dark channel constraint and alternated direction multiplier optimization of turbulence degraded image blind restoration method.First, based on the idea of multi-scale, a dark channel prior constraint is imposed on the image and non-negative constraints and energy constraints are imposed on the point spread function at each level.Then, the kernel and image of the current scale are estimated by alternating iterations of coordinate descent method. When the maximum scale is reached, the final estimated blur kernel is obtained.Last, combined with the total variational model, the image details are quickly restored using the alternate direction optimization method. The experimental results show that the prior information constraint used in the proposed algorithm is advantageous to obtain a clear solution, and can converge to the global optimal solution in the total variational model, which can effectively suppress the artifacts produced in the image restoration process and recover a better target image detail.

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