Directional fractional-order total variation hybrid regularization for image deblurring

Abstract

To overcome the staircase effect and texture loss of total variation (TV), a nonblind image deblurring method that combines the multidirectional fractional-order TV and the traditional TV is proposed. First, a four-directional fractional-order TV (FOTV4) model is put forward to explore more directional information of an image. Then the FOTV4 model and the traditional TV model are related in a unified regularization framework. Finally, the split Bregman algorithm and fast Fourier transform theory are utilized to optimize the proposed hybrid regularization model. Numerical experiments demonstrate that the proposed method can protect the texture and edge while eliminating the staircase effect effectively.