The raise of 3D image market is rapid. In previous work [Wang 2008], distortion and grid line bending constraints is adapted to image resizing while important areas remain the same scale. In another previous work [Lang 2010], disparity of input stereo image is remapped, and warped stereo image pairs are manipulated by similar constraints. In our system, we adapt image constraints similar to Lang's work, but for a depth refinement purpose. Original random and sharp depth error causes deformation and large defect of hole-filling. These errors are refined, but with a consequence of blurred depth edge. So we adapt another circuit model constraint to sharpen the depth edge again, but maintain the smoothed results at the same time. This technique is modified from previous work [Grady 2006], pixels are electrical circuit nodes with resistance derived from RGB difference. Generally, temporal smooth in video processing needs information from several frames. But in our system, no multiple frames involve but only current frame. In the same scene, different frames share similar color and shape. Since depth map is refined by 2D image, and temporal 2D images are similar, refined depths tend to be smoothed and sharpened in similar way. Finally, depth map of previous frame is used as an initial depth map of current optimization. Experiment results in Figure 1 & 2 show significant improvement.