bilateral total variation

Total fractional-order variation and bilateral filter for image denoising

Image denoising stands out as a primary goal in image processing.  However, many existing methods encounter challenges in preserving features such as corners and edges of an image while deleting the noise.  This study investigates and evaluates a fractional-order derivative based on the total $\alpha$-order variation (TV) model and the bilateral total variation (BTV) model.  This choice is motivated by the proven effectiveness of the TV model in noise removal and edge preservation, with the BTV model further utilized to enhance the restoration of fine and intricate deta

Robust approach for blind separation of noisy mixtures of independent and dependent sources

In this paper, a new Blind Source Separation (BSS) method that handles mixtures of noisy independent / dependent sources is introduced.  We achieve that by  minimizing a criterion that fuses a separating part, based on Kullback–Leibler divergence for either dependent or independent sources, with a regularization part that employs the bilateral total variation (BTV) for the purpose of denoising the observations.  The proposed algorithm utilizes a primal-dual algorithm to remove the noise, while a gradient descent method is implemented to retrieve the signal sources.  Our algorithm has shown