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Fast robust detection of edges in noisy depth images

[+] Author Affiliations
Wei Liu, Jie Yang

Shanghai Jiao Tong University, Institute of Image Processing and Pattern Recognition, 800 Dongchuan Road, Minhang District, Shanghai 200240, China

Key Laboratory of System Control and Information Processing, Ministry of Education, 800 Dongchuan Road, Minhang District, Shanghai 200240 China

Xiaogang Chen

University of Shanghai for Science and Technology, College of Communication and Art Design, 516 Jun Gong Road, Shanghai 200093, China

Qiang Wu

University of Technology Sydney, School of Computing and Communications, P.O. Box 123, Broadway, New South Wales 2007, Australia

J. Electron. Imaging. 25(5), 053003 (Sep 06, 2016). doi:10.1117/1.JEI.25.5.053003
History: Received April 10, 2016; Accepted August 10, 2016
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Abstract.  Depth edges play an important role in depth image upsampling. Many recent upsampling methods rely on the prior images of depth edges to preserve sharp depth edges in restored depth images. However, recent depth edge detection methods are not robust against the noise in depth images. Some methods are also too time-consuming. We propose a method to efficiently detect edges in depth images. The proposed method is very simple but very robust against the noise in depth images. It is also fast and has near O(1) implementation. We apply the proposed method to the existing edge guided depth image upsampling. Experimental results on both simulated and real data show the effectiveness of the proposed method.

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Citation

Wei Liu ; Xiaogang Chen ; Qiang Wu and Jie Yang
"Fast robust detection of edges in noisy depth images", J. Electron. Imaging. 25(5), 053003 (Sep 06, 2016). ; http://dx.doi.org/10.1117/1.JEI.25.5.053003


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