OPT OpenIR  > 光谱成像技术实验室
Noise-resistant matching algorithm integrating regional information for low-light stereo vision
Feng, Huahui1,2; Zhang, Geng1; Hu, Bingliang1; Zhang, Xin1; Li, Siyuan1,2,3
Department光谱成像技术实验室
2019-01
Source PublicationJOURNAL OF ELECTRONIC IMAGING
ISSN1017-9909;1560-229X
Volume28Issue:1
Contribution Rank1
Abstract

Low-light stereo vision is a challenging problem because images captured in dark environment usually suffer from strong random noises. Some widely adopted algorithms, such as semiglobal matching, mainly depend on pixel-level information. The accuracy of local feature matching and disparity propagation decreases when pixels become noisy. Focusing on this problem, we proposed a matching algorithm that utilizes regional information to enhance the robustness to local noisy pixels. This algorithm is based on the framework of ADCensus feature and semiglobal matching. It extends the original algorithm in two ways. First, image segmentation information is added to solve the problem of incomplete path and improve the accuracy of cost calculation. Second, the matching cost volume is calculated with AD-SoftCensus measure that minimizes the impact of noise by changing the pattern of the census descriptor from binary to trinary. The robustness of the proposed algorithm is validated on Middlebury datasets, synthetic data, and real world data captured by a low-light camera in darkness. The results show that the proposed algorithm has better performance and higher matching rate among top-ranked algorithms on low signal-to-noise ratio data and high accuracy on the Middlebury benchmark datasets. (C) 2019 SPIE and IS&T

Keywordstereo matching low-light random noise regional information
DOI10.1117/1.JEI.28.1.013050
Indexed BySCI
Language英语
WOS IDWOS:000460119700050
PublisherIS&T & SPIE
Citation statistics
Document Type期刊论文
Identifierhttp://ir.opt.ac.cn/handle/181661/31325
Collection光谱成像技术实验室
Corresponding AuthorLi, Siyuan
Affiliation1.Chinese Acad Sci, Xian Inst Opt & Precis Mech, Key Lab Spectral Imaging Technol CAS, Xian, Shaanxi, Peoples R China
2.Univ Chinese Acad Sci, Beijing, Peoples R China
3.Xi An Jiao Tong Univ, Xian, Shaanxi, Peoples R China
Recommended Citation
GB/T 7714
Feng, Huahui,Zhang, Geng,Hu, Bingliang,et al. Noise-resistant matching algorithm integrating regional information for low-light stereo vision[J]. JOURNAL OF ELECTRONIC IMAGING,2019,28(1).
APA Feng, Huahui,Zhang, Geng,Hu, Bingliang,Zhang, Xin,&Li, Siyuan.(2019).Noise-resistant matching algorithm integrating regional information for low-light stereo vision.JOURNAL OF ELECTRONIC IMAGING,28(1).
MLA Feng, Huahui,et al."Noise-resistant matching algorithm integrating regional information for low-light stereo vision".JOURNAL OF ELECTRONIC IMAGING 28.1(2019).
Files in This Item:
File Name/Size DocType Version Access License
Noise-resistant matc(4560KB)期刊论文出版稿开放获取CC BY-NC-SAView Application Full Text
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Feng, Huahui]'s Articles
[Zhang, Geng]'s Articles
[Hu, Bingliang]'s Articles
Baidu academic
Similar articles in Baidu academic
[Feng, Huahui]'s Articles
[Zhang, Geng]'s Articles
[Hu, Bingliang]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Feng, Huahui]'s Articles
[Zhang, Geng]'s Articles
[Hu, Bingliang]'s Articles
Terms of Use
No data!
Social Bookmark/Share
File name: Noise-resistant matching algorithm integrating regional information for low-light stereo vision.pdf
Format: Adobe PDF
All comments (0)
No comment.
 

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