标题:Stream Model-Based Orthorectification in a GPU Cluster Environment

作者:Lei, Z (Lei, Zhen); Wang, M (Wang, Mi); Li, DR (Li, Deren); Lei, TL (Lei, Ting L.)

卷:11 期:12 页:2115-2119 DOI:10.1109/LGRS.2014.2320991 出版年:DEC 2014

摘要:One of the most important tasks in remote sensing data processing is the production of orthorectified images. Such tasks are computationally intensive and can become a bottleneck for remote sensing image processing, particularly in high-throughput environments, such as large satellite imagery processing centers. This letter explores the use of massive parallel processing graphical processing unit (GPU) in a clustered network environment to speed up image processing tasks, such as orthorectification. Our parallelization method is based on inverse sensor model and the stream model for image processing, which allow the flexibility of placing computational units on proper computation units, such as GPU, CPU cores, or nodes in a cluster. In our experiments on images of two satellites, more than 198 times and 50.3 times speedup over one and multiple thread CPU versions have been achieved, respectively.

地址:[Lei, Zhen; Wang, Mi; Li, Deren] Wuhan Univ, Lab Informat Engn Surveying Mapping & Remote Sens, Wuhan 430079, Peoples R China.

[Lei, Ting L.] Univ S Carolina, Columbia, SC 29208 USA.

通讯作者地址:Wang, M (通讯作者),Wuhan Univ, Lab Informat Engn Surveying Mapping & Remote Sens, Wuhan 430079, Peoples R China.

电子邮件地址:leizhen@gmail.com; wangmi@whu.edu.cn; drli@whu.edu.cn; tingle.geog@gmail.com

ISSN:1545-598X

电子 ISSN:1558-0571