OPT OpenIR  > 光谱成像技术实验室
A Noise-Resistant Stereo Matching Algorithm Integrating Regional Information
Feng Huahui1; Zhang Geng2; Zhang Xin2; Hu Bingliang2
2018
会议名称3rd IEEE International Conference on Image, Vision and Computing (ICIVC)
会议录名称2018 IEEE 3RD INTERNATIONAL CONFERENCE ON IMAGE, VISION AND COMPUTING (ICIVC)
页码952-955
会议日期2018-06-27
会议地点Chongqing, PEOPLES R CHINA
出版者IEEE
产权排序1
摘要

Focusing on the problem existing in stereo matching that low-SNR image, such as images collected at night, we propose a novel matching framework based on semi-global matching algorithm and AD-Census. This algorithm extends the original algorithms in two ways. First, image segmentation information as an additional constraint is added that 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 on the quality of matching by changing the pattern of census descriptor from binary to trinary. Results of Middlebury standard test data show that the algorithm significantly improves the precision of matching. In addition, a low-light binocular platform is built to test our method in night environment. Results show the disparity maps are more accurate compared to previous methods.

作者部门光谱成像技术实验室
收录类别CPCI
ISBN号978-1-5386-4991-6
语种英语
WOS记录号WOS:000448170000185
引用统计
文献类型会议论文
条目标识符http://ir.opt.ac.cn/handle/181661/30709
专题光谱成像技术实验室
通讯作者Feng Huahui
作者单位1.Univ Chinese Acad Sci, Xian Inst Opt & Precis Mech, Xian, Shaanxi, Peoples R China
2.Xian Inst Opt & Precis Mech, Xian, Shaanxi, Peoples R China
推荐引用方式
GB/T 7714
Feng Huahui,Zhang Geng,Zhang Xin,et al. A Noise-Resistant Stereo Matching Algorithm Integrating Regional Information[C]:IEEE,2018:952-955.
条目包含的文件
文件名称/大小 文献类型 版本类型 开放类型 使用许可
A Noise-Resistant St(792KB)会议论文 开放获取CC BY-NC-SA请求全文
个性服务
推荐该条目
保存到收藏夹
查看访问统计
导出为Endnote文件
谷歌学术
谷歌学术中相似的文章
[Feng Huahui]的文章
[Zhang Geng]的文章
[Zhang Xin]的文章
百度学术
百度学术中相似的文章
[Feng Huahui]的文章
[Zhang Geng]的文章
[Zhang Xin]的文章
必应学术
必应学术中相似的文章
[Feng Huahui]的文章
[Zhang Geng]的文章
[Zhang Xin]的文章
相关权益政策
暂无数据
收藏/分享
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。