Region-based depth recovery for highly sparse depth maps
Said D. Pertuz, Joni Kämäräinen · 2017
The accurate recovery of missing values in depth maps is an important problem in computer vision and image processing. In depth maps with large, irregular missing regions (i.e., sparse depth maps) inaccuracies arise when depth values of known pixels are used to recover depth near object edges and depth discontinuities (leakage). In order to overcome this problem, we propose an iterative region-based depth recovery method. In the proposed approach, the depth recovery problem is solved iteratively for each region of the segmented image in order to reduce the effect of leakage. Quantitative and qualitative experiments conducted on real data sets show promising results when comparing the proposed approach with state-of-the-art methods.