Image Zooming Technique Based on the Split Bregman Iteration with Fractional Order Variation Regularization

Liping Wang, Shangbo Zhou and Awudu Karim College of Computer Science, Chongqing University, China

Abstract: It is always a challenging work to develop an accurate and effective method to reconstruct a degraded image. In this paper, the nonlocal variation Fractional Total Variation (FTV) regularization technique for image zooming is investigated. To enhance edges, yet preserve textures, fractional order calculus based image zooming method is proposed, which can deal well with fine structures like textures. To solve the nonlinear Euler-Lagrange equation associated with the nonlocal variation FTV regularization model, we propose a nonlocal total variation method for image zooming based on the split Bregman iteration. Enlarging and de-noising experimental results show that the proposed method has effectiveness and reliability by comparing to some methods mentioned in the paper.

Keywords: Image zooming, total variation, split bregman iteration, fractional order.