Improved TV for blind deblurring with split Bregman iteration

Abstract

In this paper, an improved TV (total variation) with split Bregman iteration is proposed to improve the result of blind image deblurring. According to the property of the higher partial derivatives in the local image, adaptive values of regularisation parameters in TV algorithm are calculated in order to suppress the ringing artefacts effectively. To alleviate the difficulty of L₁ norm problem, the split Bregman iteration is also adopted. Comparisons are made between the proposed and traditional methods, and experimental results prove that the proposed algorithm is not only robust to different size of blur kernels, but also can suppress the ringing artefacts to a great extent in the latent image, both visually and theoretically.

Keywords:

• Blind deblurring
• Kernel estimation
• Total variation
• Motion blur
• Split Bregman iteration

Acknowledgements

The research work was supported by the National Natural Science Foundation of China (Grant No. 61401439, 61573114), Project of Tianjin Application Foundation and Advanced Technology Research Program (15JCYBJC16600).