Parallel Processing of Massive Remote Sensing Images in a GPU Architecture
Peng Liu; Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, No. 9 Dengzhuang South Road, Haidian District, Beijing 100094 ; Tao Yuan; Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, No. 9 Dengzhuang South Road, Haidian District, Beijing 100094 ; Yan Ma; Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, No. 9 Dengzhuang South Road, Haidian District, Beijing 100094 ; Lizhe Wang; Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, No. 9 Dengzhuang South Road, Haidian District, Beijing 100094 ; Dingsheng Liu; Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, No. 9 Dengzhuang South Road, Haidian District, Beijing 100094 ; Shasha Yue; Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, No. 9 Dengzhuang South Road, Haidian District, Beijing 100094 ; Joanna Kołodziej; Institute of Computer Science, Cracow University of Technology, Warszawska 24, 31-155 Cracow
Computing and Informatics, Tome 33 (2014) no. 1, / Harvested from Computing and Informatics
Text on Computing and Informatics
Profiting from the development of space remote sensing technology, the amount of remote sensing image data obtained by satellite is increasing dramatically; however, how to deal with these data quickly and efficiently has turned out to be a great computational challenge. With the rapid development of general-purpose GPU computing technology, researchers improved remote sensing applications based on GPU, and obtained good speedup. However, the current GPU parallel processes are not well adapted to the remote sensing image processing; furthermore, they have data loading, storage, and I/O problems. To solve these bottlenecks, this paper proposes three corresponding optimization strategies, and their effectiveness is confirmed by further experiments.
Publié le : 2014-06-03
Classification:  GPU, remote sensing image processing, data intensive computing 
@article{cai2388,
     author = {Peng Liu; Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, No. 9 Dengzhuang South Road, Haidian District, Beijing 100094 and Tao Yuan; Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, No. 9 Dengzhuang South Road, Haidian District, Beijing 100094 and Yan Ma; Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, No. 9 Dengzhuang South Road, Haidian District, Beijing 100094 and Lizhe Wang; Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, No. 9 Dengzhuang South Road, Haidian District, Beijing 100094 and Dingsheng Liu; Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, No. 9 Dengzhuang South Road, Haidian District, Beijing 100094 and Shasha Yue; Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, No. 9 Dengzhuang South Road, Haidian District, Beijing 100094 and Joanna Ko\l odziej; Institute of Computer Science, Cracow University of Technology, Warszawska 24, 31-155 Cracow},
     title = {Parallel Processing of Massive Remote Sensing Images in a GPU Architecture},
     journal = {Computing and Informatics},
     volume = {33},
     number = {1},
     year = {2014},
     language = {en},
     url = {http://dml.mathdoc.fr/item/cai2388}
}

Peng Liu; Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, No. 9 Dengzhuang South Road, Haidian District, Beijing 100094; Tao Yuan; Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, No. 9 Dengzhuang South Road, Haidian District, Beijing 100094; Yan Ma; Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, No. 9 Dengzhuang South Road, Haidian District, Beijing 100094; Lizhe Wang; Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, No. 9 Dengzhuang South Road, Haidian District, Beijing 100094; Dingsheng Liu; Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, No. 9 Dengzhuang South Road, Haidian District, Beijing 100094; Shasha Yue; Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, No. 9 Dengzhuang South Road, Haidian District, Beijing 100094; Joanna Kołodziej; Institute of Computer Science, Cracow University of Technology, Warszawska 24, 31-155 Cracow. Parallel Processing of Massive Remote Sensing Images in a GPU Architecture. Computing and Informatics, Tome 33 (2014) no. 1, . http://gdmltest.u-ga.fr/item/cai2388/