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Disocclusion Hole-Filling in DIBR-Synthesized Images using Multi-Scale Template Matching

Reel, S.; Wong, K. C. P.; Cheung, G. and Dooley, L. S. (2014). Disocclusion Hole-Filling in DIBR-Synthesized Images using Multi-Scale Template Matching. In: Visual Communications and Image Processing Conference, 2014 IEEE, IEEE, pp. 494–497.

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Transmitting texture and depth images of captured camera view(s) of a 3D scene enables a receiver to synthesize novel virtual viewpoint images via Depth-Image-Based Rendering (DIBR). However, a DIBR-synthesized image often contains disocclusion holes, which are spatial regions in the virtual view image that were occluded by foreground objects in the captured camera view(s). In this paper, we propose to complete these disocclusion holes by exploiting the self-similarity characteristic of natural images via nonlocal template-matching (TM). Specifically, we first define self-similarity as nonlocal recurrences of pixel patches within the same image across different scales--one characterization of self-similarity in a given image is the scale range in which these patch recurrences take place. Then, at encoder we segment an image into multiple depth layers using available per-pixel depth values, and characterize self-similarity in each layer with a scale range; scale ranges for all layers are transmitted as side information to the decoder. At decoder, disocclusion holes are completed via TM on a per-layer basis by searching for similar patches within the designated scale range. Experimental results show that our method improves the quality of rendered images over previous disocclusion hole-filling algorithms by up to 3.9dB in PSNR.

Item Type: Conference or Workshop Item
Copyright Holders: 2014 IEEE
ISBN: 1-4799-6139-6, 978-1-4799-6139-9
Keywords: free viewpoint video; depth-image-based rendering; image inpainting
Academic Unit/School: Faculty of Science, Technology, Engineering and Mathematics (STEM) > Computing and Communications
Faculty of Science, Technology, Engineering and Mathematics (STEM)
Research Group: Centre for Research in Computing (CRC)
Related URLs:
Item ID: 41031
Depositing User: Smarti Reel
Date Deposited: 02 Oct 2014 09:47
Last Modified: 07 Dec 2018 14:49
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