Adaptive Parameter Selection Method Based on Total Variation Model

As for the disadvantage of not being able to adaptively adjust the regularization parameters in the total variation model, an adaptive dual projection algorithm was proposed based on Chambolle's dual algorithm. With the fixed point iteration theory, the relationship among weights, regularization term and approximation term was built, and the update criterion of weight was obtained. For the proposed parameter selection problem, the multiple linear regression model was used to fit the selection model of new parameter. The potential of the proposed method was verified through the significance test. The experimental results show that the algorithm is effective in improving the denoising effect.