Super-resolution image reconstruction method using homotopy regularization

In this paper, we present a homotopy regularization based on fractional order total variation for image super-resolution. This regularization function of the proposed method is composed of three parts: fractional order TV regularization term, homotopy data fidelity term and traditional data fidelity. And the overall function is minimized using the gradient descent flow. For super-resolution reconstruction, the proposed approach makes full use of characteristics of fractional calculus and homotopy method, avoiding effectively the jaggies when reconstructing an image. Fractional calculus can significantly improve high frequency component of a signal, while the low frequency part is strengthened accordingly. Homotopy method can achieve convergence quickly in a nonlocal area.