A Depth Map Post-Processing Approach Based on Adaptive Random Walk With Restart

IEEE Access

Hossein Javidnia¹  Peter Corcoran¹ 

[1] Department of Electronic Engineering, College of Engineering, National University of Ireland, Galway, Ireland;

关键词: Stereo matching;    depth map;    accuracy;    edge preserving;   

DOI  :  10.1109/ACCESS.2016.2603220

来源: DOAJ

【 摘 要 】

Accurate depth estimation is still an important challenge after a decade, particularly from stereo images. The accuracy comes from a good depth level and preserved structure. For this purpose, a depth post-processing framework is proposed in this paper. The framework starts with the “Adaptive Random Walk with Restart (2015)” algorithm. To refine the depth map generated by this method, we introduced a form of median solver/filter based on the concept of the mutual structure, which refers to the structural information in both images. This filter is further enhanced by a joint filter. Next, a transformation in image domain is introduced to remove the artifacts that cause distortion in the image. The proposed post-processing method is then compared with the top eight algorithms in the Middlebury benchmark. To explore how well this method is able to compete with more widely known techniques, a comparison is performed with Google's new depth map estimation method. The experimental results demonstrate the accuracy and efficiency of the proposed post-processing method.

【 授权许可】

Unknown