Intensity-guided edge-preserving depth upsampling through weighted L0 gradient minimization

Depth is an important visual cue to perceive real-world scenes. Although a time-of-flight (ToF) depth camera can provide depth information in dynamic scenes, captured depth images are often noisy and of low resolution. In this paper, we propose an intensity-guided edge-preserving depth upsampling method through weighted L-0 gradient minimization to enhance both resolution and visual quality of depth images. Guided by the high-resolution intensity image, we perform optimization to preserve boundaries of objects. We apply L-0 gradient to the regularization term, and compute its weight from both intensity and depth images. We optimize the objective function using alternating minimization and half-quadratic splitting. Experimental results on Middlebury 2005, 2014, and real-world scene datasets demonstrate that the proposed method produces boundary-preserving depth upsampling results and outperforms state-of-the-art ones in terms of accuracy. (C) 2016 Elsevier Inc. All rights reserved.