Image restoration using majorization-minimizaiton algorithm based on generalized total variation
优化-最小求解的广义总变分图像复原

Total variation (TV) regularization is an effective tool to resolve ill-posed problem in image restoration. But the TV only considers the first order variation with the higher order variations ignored. Furthermore, the form of TV induces a difficulty in optimization. Accordingly, a method of image restoration based on generalized TV (GTV) using MM algorithm is proposed to overcome the problems of TV. The GTV has not only the heavy tail property of TV, but also bilateral weights of bilateral TV (BTV). In fact, it is an extended form of the TV. For the optimization problem of GTV, we adopt the majorization-minimization (MM) algorithm to overcome its difficulty. Experimental results show that the proposed method achieves effective performance with about 2dB ISNR (improvement of SNR).