Multimodal polarization image simulated crater detection
文献类型:期刊论文
作者 | Zhang, Xin2![]() ![]() ![]() |
刊名 | JOURNAL OF ELECTRONIC IMAGING
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出版日期 | 2020-03-01 |
卷号 | 29 |
关键词 | target detection polarization characteristics multimodal fusion simulated crater |
ISSN号 | 1017-9909 |
DOI | 10.1117/1.JEI.29.2.023027 |
通讯作者 | Zhang, Jingjing(fannyzjj@ahu.edu.cn) |
英文摘要 | Most previous target detection methods are based on the physical properties of visible-light polarization images, depending on different targets and backgrounds. However, this process is not only complicated but also vulnerable to environmental noises. A multimodal fusion detection network based on the multimodal deep neural network architecture is proposed in this research. The multimodal fusion detection network integrates the high-level semantic information of visible-light polarization image in crater detection. The network contains the base network, the fusion network, and the detection network. Each of the base networks outputs a corresponding feature figure of polarization image, fused by the fusion network later to output a final fused feature figure, which is input into the detection network to detect the target in the image. To learn target characteristics effectively and improve the accuracy of target detection, we select the base network by comparing between VGG and ResNet networks and adopt the strategy of model parameter pretraining. The experimental results demonstrate that the simulated crater detection performance of the proposed method is superior to the traditional and single-modal-based methods in that the extracted polarization characteristics are beneficial to target detection. (C) The Authors. Published by SPIE under a Creative Commons Attribution 4.0 Unported License. |
资助项目 | Anhui Provincial Natural Science Foundation[1808085MF209] ; Open Research Foundation of Key Laboratory of Polarization Imaging Detection Technology Anhui Province[2019KJS030009] ; Open Research Foundation of Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education ; Guangzhou Science and Technology Plan Project Funding, China[201907010020] |
WOS研究方向 | Engineering ; Optics ; Imaging Science & Photographic Technology |
语种 | 英语 |
WOS记录号 | WOS:000531056800027 |
出版者 | IS&T & SPIE |
资助机构 | Anhui Provincial Natural Science Foundation ; Open Research Foundation of Key Laboratory of Polarization Imaging Detection Technology Anhui Province ; Open Research Foundation of Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education ; Guangzhou Science and Technology Plan Project Funding, China |
源URL | [http://ir.hfcas.ac.cn:8080/handle/334002/103287] ![]() |
专题 | 中国科学院合肥物质科学研究院 |
通讯作者 | Zhang, Jingjing |
作者单位 | 1.Chinese Acad Sci, Anhui Inst Opt & Fine Mech, Key Lab Opt Calibrat & Characterizat, Hefei, Peoples R China 2.Anhui Univ, Sch Elect Engn & Automat, Key Lab Intelligent Comp & Signal Proc, Minist Educ, Hefei, Peoples R China 3.Key Lab Polarized Light Imaging & Detect Technol, Hefei, Anhui, Peoples R China 4.Guangzhou & Chinese Acad Sci, Inst Software Applicat Technol, Guangzhou, Peoples R China |
推荐引用方式 GB/T 7714 | Zhang, Xin,Zhang, Jingjing,Wang, Feng,et al. Multimodal polarization image simulated crater detection[J]. JOURNAL OF ELECTRONIC IMAGING,2020,29. |
APA | Zhang, Xin,Zhang, Jingjing,Wang, Feng,Liu, Xiao,Wu, Jun,&Li, Teng.(2020).Multimodal polarization image simulated crater detection.JOURNAL OF ELECTRONIC IMAGING,29. |
MLA | Zhang, Xin,et al."Multimodal polarization image simulated crater detection".JOURNAL OF ELECTRONIC IMAGING 29(2020). |
入库方式: OAI收割
来源:合肥物质科学研究院
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