CASIA OpenIR  > 复杂系统管理与控制国家重点实验室  > 复杂系统研究
MRF-Based Disparity Upsampling Using Stereo Confidence Evaluations
Meng, Xiangbing1,2; Zhang, Zhaoxing1; Geng, Zheng1; Zhang, Mei1; Zhang M (张梅)
AbstractDisparity upsampling methods are derived for restoring high-quality disparity maps from active three-dimensional imaging techniques such as time-of-flight method. Although effective, traditional upsampling methods exhibit certain drawbacks. For example, noisy disparity values in the low-scaled level are taken indiscriminately to carry out the upsampling assignment, which could lead to dramatically weakened results. To solve this problem, we herein present a Markov random field ( MRF) based disparity upsampling method using confidence evaluations. We utilize confidence measures under the stereo configuration to evaluate the reliability of disparity value. The confidence maps are then properly integrated into the state-of-the-artMRF-based depth upsampling (MBU) method to constrain the negative effect caused by the noisy disparity. More specifically, the confidence is used to remove unqualified pixels from participating in the disparity upsampling computation. Extensive experiments were performed to validate the proposed new method. In these experiments, initial low-scaled disparity maps were from either ground truth or stereo matching methods. Results verified that our method can obtain significantly better upsampled disparity maps than that from the original MBU or other nonconfidence-based methods. In addition, we implemented our algorithms on general public utilities to improve the execution speed.
Other Abstract无 
KeywordConfidence Evaluation Disparity Upsampling Markov Random Field (Mrf) Noise Three-dimensional (3-d) Reconstruction
WOS HeadingsScience & Technology ; Technology
Indexed BySCI
Funding OrganizationNational High-tech R&D Program (863 Program) of China(2015AA015905) ; National Natural Science Foundation of China(61605240)
WOS Research AreaEngineering
WOS SubjectEngineering, Electrical & Electronic
WOS IDWOS:000427642600007
Citation statistics
Cited Times:1[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Corresponding AuthorZhang M (张梅)
Affiliation1.Chinese Acad Sci, Inst Automat, State Key Lab Management & Control Complex Syst, Beijing 100049, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100190, Peoples R China
First Author AffilicationInstitute of Automation, Chinese Academy of Sciences
Recommended Citation
GB/T 7714
Meng, Xiangbing,Zhang, Zhaoxing,Geng, Zheng,et al. MRF-Based Disparity Upsampling Using Stereo Confidence Evaluations[J]. IEEE SIGNAL PROCESSING LETTERS,2018,25(4):561-565.
APA Meng, Xiangbing,Zhang, Zhaoxing,Geng, Zheng,Zhang, Mei,&Zhang M .(2018).MRF-Based Disparity Upsampling Using Stereo Confidence Evaluations.IEEE SIGNAL PROCESSING LETTERS,25(4),561-565.
MLA Meng, Xiangbing,et al."MRF-Based Disparity Upsampling Using Stereo Confidence Evaluations".IEEE SIGNAL PROCESSING LETTERS 25.4(2018):561-565.
Files in This Item: Download All
File Name/Size DocType Version Access License
08240719MXB.pdf(1065KB)期刊论文作者接受稿开放获取CC BY-NC-SAView Download
Related Services
Recommend this item
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Meng, Xiangbing]'s Articles
[Zhang, Zhaoxing]'s Articles
[Geng, Zheng]'s Articles
Baidu academic
Similar articles in Baidu academic
[Meng, Xiangbing]'s Articles
[Zhang, Zhaoxing]'s Articles
[Geng, Zheng]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Meng, Xiangbing]'s Articles
[Zhang, Zhaoxing]'s Articles
[Geng, Zheng]'s Articles
Terms of Use
No data!
Social Bookmark/Share
File name: 08240719MXB.pdf
Format: Adobe PDF
All comments (0)
No comment.

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.