Abstract:

View on the weakness of a classical variational denoising model in which edge information is sensitive to noises and prone to blur, two improved nonlinear and linear weighted variational algorithms are put forward. In the nonlinear weighted variational model, a weight function is introduced in the regularization term of the classical model to induct diffusion, which gives the result that the new model preserves the texture characteristics and the edge information better while removing noises. In the linear model, the Gaussian function is used to smooth the noised image before diffusion, which reduces the computational complexity. Compared with the classical model, the experimental results show improvements of both the proposed models.