Depth map up-sampling with texture edge feature via sparse representation
Depth information has been an important part in various computer vision applications. However, the low resolution depth map captured by TOF cameras and other depth sensors cannot be directly used in visual depth perception and 3D reconstruction. Thus, this paper proposes an effective depth map up-sampling algorithm which reconstructs a high resolution depth map from a low depth map, by integrating the registered color image. Different from the other depth map up-sampling methods, we establish the correspondence between the high resolution and low resolution image pairs via image sparse representation, then extract the geometric structure component and texture component from high resolution depth map and the relevant color image, respectively. Specially, we employ a guided filter to preserve regions smooth and edges sharp. The experimental results show that the proposed depth map up-sampling method obtains quality improvement on depth map and the synthesized view compared with state-of-the-art methods.