A foreground biased depth map refinement method for DIBR view synthesis

Xu, Xuyuan; Po, Lai-Man; Cheung, Kmc; Ng, Ka-Ho; Wong, Kwok-Wo

doi:10.1109/icassp.2012.6288006

Cited by 18 publications

(9 citation statements)

References 7 publications

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“…5b. The size of the disocclusion region is determined by the value of d f (x, y), and the quantitative relationship between them can be found in [29]. In Fig.…”

Section: Proposed Methodsmentioning

confidence: 99%

“…Several methods for solving this problem have been proposed, which can be categorized into two classes: (1) depth map preprocessing before rendering [10,13,14,29,30] and (2) image inpainting jointing depth and texture information after rendering [6,17,19,21,24]. In this paper, we focus on the former class, which mainly consists of depth filtering and depth boundary refinement.…”

mentioning

confidence: 99%

“…However, depth filtering usually introduces rubber-sheet artifacts and geometric distortions. Another method applied is the dilation of the FG objects of the depth map [13,29,30]. In [29], a dilation based method for view synthesis by DIBR was proposed.…”

mentioning

confidence: 99%

“…Another method applied is the dilation of the FG objects of the depth map [13,29,30]. In [29], a dilation based method for view synthesis by DIBR was proposed. The depth pixels which located in the large depth discontinuities are refined with the neighboring foreground depth values, and thus improve the quality of the rendered virtual view.…”

mentioning

confidence: 99%

“…The depth pixels which located in the large depth discontinuities are refined with the neighboring foreground depth values, and thus improve the quality of the rendered virtual view. In [30], Xu et al extended the method in [29] with a misalignment correction of the depth map for a better view synthesis result. Koppel et al [13] proposed a depth preprocessing method which including the depth map dilation, adaptive cross-trilateral median filtering, and adaptive temporally consistent asymmetric smoothing filtering to reduce holes and distortions in the virtual view.…”

mentioning

confidence: 99%

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A divide-and-conquer hole-filling method for handling disocclusion in single-view rendering

Lei

Zhang

et al. 2016

Multimed Tools Appl

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Large holes are unavoidably generated in depth image based rendering (DIBR) using a single color image and its associated depth map. Such holes are mainly caused by disocclusion, which occurs around the sharp depth discontinuities in the depth map. We propose a divide-and-conquer hole-filling method which refines the background depth pixels around the sharp depth discontinuities to address the disocclusion problem. Firstly, the disocclusion region is detected according to the degree of depth discontinuity, and the target area is marked as a binary mask. Then, the depth pixels located in the target area are modified by a linear interpolation process, whose pixel values decrease from the foreground depth value to the background depth value. Finally, in order to remove the isolated depth pixels, median filtering is adopted to refine the depth map. In these ways, disocclusion regions in the synthesized view are divided into several small holes after DIBR, and are easily filled by image inpainting. Experimental results demonstrate that the proposed method can effectively improve the quality of the synthesized view subjectively and objectively.

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“…5b. The size of the disocclusion region is determined by the value of d f (x, y), and the quantitative relationship between them can be found in [29]. In Fig.…”

Section: Proposed Methodsmentioning

confidence: 99%