The resolution of depth image is very low. In this paper

with a registered and potentially high resolution color image of the same scene

we propose a second order total generalized variation super-resolution method based on color image regularization terms. First

the low-resolution depth image is mapped onto the high-resolution color image coordinate system. Then

the second-order total generalized variation model is used and the high-resolution image constrained term with an edge indicator function is used to construct the regularization term. The depth map super-resolution problem is solved by developing an energy optimization framework. Finally

the reweighted method and primal-dual method are used to solve the energy function. The experimental results demonstrate that the proposed approach can well preserve the edge information and obtain a high resolution depth image in terms of both its spatial resolution and depth precision. The proposed method can effectively solve the problem of low depth image resolution.