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Gradient-domain-based enhancement of multi-view depth video.pdf
Information Sciences 281 (2014) 750–761
Contents lists available at ScienceDirect
Information Sciences
journal homepage: /locate/ins
Gradient-domain-based enhancement of multi-view depth video
Qiong Liu a,?, Zhengjun Zha b, Yang Yang b
a Department of Electronic and Information Engineering, Huazhong University of Science and Technology, Wuhan, China b School of Computing, National University of Singapore, Singapore
article info
Article history: Received 22 February 2013 Received in revised form 20 April 2014 Accepted 26 April 2014 Available online 9 May 2014
Keywords: Depth enhancement Multi-view depth video Image processing Three-dimensional video
abstract
Multi-view depth is an emerging and attractive 3D representation in recent years, which acts a signi?cant role in rendering numerous viewing angles from a small number of given input views. The performance of those depth-based 3D video applications is strongly dependent on the quality of multi-view depth. However, because of the limitations of depth acquisition and estimation, the quality of multi-view depth suffers from artifacts in spatial dimension and inconsistency in both the temporal and inter-view dimensions. In this paper, we propose a gradient-domain based enhancement method for multi-view depth. Being different from the traditional enhancement methods which intended to process one or two above dimensions, our proposal exploits the coherence of both temporal and inter-view dimensions in addition of the spatial one. It is very challenging to obtain the stable characteristics in multi-dimensions. To solve this problem, we propose to investigate the characteristics in the gradient domain rather than the intensity domain. The enhanced multi-view depth is obtained through the minimization of energy function under the constraint of a joint gradient ?eld (JGF), which is estimated from multiple dimensions through motion estimation and geometric mapping. Therefore, the enhanced multi-view depth is a global optimi
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