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Unsupervised variational auto-encoder hash algorithm based on multi-channel feature fusion
Wang, Huanting1,2; Qu, Bo1; Lu, Xiaoqiang1; Chen, Yaxiong1,2
2020
会议名称12th International Conference on Digital Image Processing, ICDIP 2020
会议录名称Twelfth International Conference on Digital Image Processing, ICDIP 2020
卷号11519
会议日期2020-05-19
会议地点Osaka, Japan
出版者SPIE
产权排序1
摘要

Hashing technology is widely used to solve the problem of large-scale Remote Sensing (RS) image retrieval due to its high speed and low memory. Among the existing hashing algorithm, the unsupervised method is widely used in largescale RS image retrieval. However, the existing unsupervised RS image retrieval methods do not consider the multichannel properties of multi-spectral RS images and the discriminability in the local preservation mapping process adequately, which make it difficult to satisfy the retrieval performance of RS data. To solve these problems, we propose an unsupervised Variational Auto-Encoder Hashing algorithm based on multi-channel feature fusion (VAEH). MultiChannel Feature Fusion (MCFF) is used to extract the feature information of image, which fully considers the multichannel properties of the multi-spectral RS image. In order to enhance the discriminability in the local preservation mapping process, variational construction process and automatic encoder are added into the learning process of hashing function, and the KL distance of the Variational Auto-Encoder (VAE) is used to constrain the hashing code. Experiments on two large public RS image data sets (i.e. SAT-4 and SAT-6) have shown that our VAEH method outperforms the state of the art. © 2020 SPIE.

关键词Multi-channel feature fusion Unsupervised hashing algorithm VAE Image retrieval
作者部门光谱成像技术研究室
DOI10.1117/12.2573106
收录类别EI ; CPCI
ISBN号9781510638457
语种英语
ISSN号0277786X;1996756X
WOS记录号WOS:000589893500053
EI入藏号20202908951759
引用统计
文献类型会议论文
条目标识符http://ir.opt.ac.cn/handle/181661/93606
专题光谱成像技术研究室
作者单位1.Key Laboratory of Spectral Imaging Technology CAS, Xi'An Institute of Optics and Precision Mechanics, Chinese Academy of Sciences, Xi'an, Shaanxi; 710119, China;
2.University of Chinese Academy of Sciences, Beijing; 100049, China
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Wang, Huanting,Qu, Bo,Lu, Xiaoqiang,et al. Unsupervised variational auto-encoder hash algorithm based on multi-channel feature fusion[C]:SPIE,2020.
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