Multi-layer composite autoencoders for semi-supervised change detection in heterogeneous remote sensing images  

作　　者：Jiao SHI Tiancheng WU Hanwen YU A.K.QIN Gwanggil JEON Yu LEI 

机构地区：[1]School of Electronics and Information,Northwestern Polytechnical University,Xi'an 710129,China [2]School of Resources and Environment,University of Electronic Science and Technology of China,Chengdu 611731,China [3]Department of Computer Science and Software Engineering,Swinburne University of Technology,Melbourne 3122,Australia [4]Department of Embedded Systems Engineering,Incheon National University,Incheon 22012,Republic of Korea

出　　处：《Science China(Information Sciences)》2023年第4期120-121,共2页中国科学（信息科学）（英文版）

基　　金：supported by National Natural Science Foundation of China (Grant No. 62076204)。

摘　　要：With the increasing complexity of application scenarios,the fusion of different remote sensing data types has gradually become a trend,which can greatly improve the utilization of massive remote sensing data.While the problem of change detection for heterogeneous remote images can be much more complicated than the traditional change detection for homologous remote sensing images,there are huge differences between heterogeneous images caused by factors such as the light sensitivity and object reflection properties[1,2].So the common methods are meant to align the images from two different domains and then compare the original data in the common domain to highlight the difference[3].

关 键 词：images COMPOSITE MASSIVE 

分 类 号：TP751[自动化与计算机技术—检测技术与自动化装置]