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Fast Minimax Path-Based Joint Depth Interpolation
Longquan Dai; Feihu Zhang; Xing Mei; Xiaopeng Zhang
Source PublicationIEEE Signal Processing Letters
2015-05
Volume22Issue:5Pages:623-627
AbstractWe propose a fast minimax path-based depth interpolation method. The algorithm computes for each target pixel varying contributions from reliable depth seeds, and weighted averaging is used to interpolate missing depths. Compared with state-of-the-art joint geodesic upsampling method which selects the K nearest seeds to interpolate missing depths with O(Kn) complexity, our method does not need to limit the number of
seeds to K  and reduces the computational complexity to O(n). In addition, the minimax path chooses a path with the smallest maximum immediate pairwise pixel difference on it, so it tends to preserve sharp depth discontinuities better. In contrast to the results of previous depth upsampling algorithms, our approach can provide accurate depths with fewer artifacts.
KeywordDepth Map Minimax Path Upsampling
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/19929
Collection模式识别国家重点实验室_多媒体计算与图形学
AffiliationInstitute of Automation Chinese Academy of Sciences, Beijing, China
Recommended Citation
GB/T 7714
Longquan Dai,Feihu Zhang,Xing Mei,et al. Fast Minimax Path-Based Joint Depth Interpolation[J]. IEEE Signal Processing Letters,2015,22(5):623-627.
APA Longquan Dai,Feihu Zhang,Xing Mei,&Xiaopeng Zhang.(2015).Fast Minimax Path-Based Joint Depth Interpolation.IEEE Signal Processing Letters,22(5),623-627.
MLA Longquan Dai,et al."Fast Minimax Path-Based Joint Depth Interpolation".IEEE Signal Processing Letters 22.5(2015):623-627.
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