A Variational Model for Staircase Reduction in Image Denoising

We propose a new variational model to reduce the staircase that often appears in Total variation (TV) based models in image denoising. The model uses BV-seminorm and Besov-seminorm to measure the piece-wise constant component and piecewise smooth component of the image, respectively. We discuss the nontrivial prop-erty of the proposed model and introduce an alternating iteration algorithm that combines the dual projection al-gorithm with Wavelet soft thresholding (WST) algorithm to solve the model numerically. The experimental results show that the proposed model is effective for noise removal and staircase reduction, while the contour can be preserved in the denoised images. Furthermore, compared with two classical staircase reduction models, CEP2 and TGV, the proposed model is much faster than these two models.