A Total Variation Denoising Method Based on Median Filter and Phase Consistency
This work addresses image denoising for applications like medical imaging or photography, but it is incremental as it builds on existing total variation methods with specific modifications.
The authors tackled the problem of image noise suppression with total variation methods, which often lose details and are sensitive to parameters, by proposing the MPC-TV method that modifies total variation using a diffusion rate adjuster and a fusion filter; experimental results show it effectively suppresses noise, particularly speckle noise, and improves robustness to iteration time for noise with different variances.
The total variation method is widely used in image noise suppression. However, this method is easy to cause the loss of image details, and it is also sensitive to parameters such as iteration time. In this work, the total variation method has been modified using a diffusion rate adjuster based on the phase congruency and a fusion filter of median filter and phase consistency boundary, which is called the MPC-TV method. Experimental results indicate that MPC-TV method is effective in noise suppression, especially for the removing of speckle noise, and it can also improve the robustness of iteration time of TV method on noise with different variance.