GPGC: a Grid-enabled parallel algorithm of geometric correction for remote-sensing applications

摘要

ChinaGrid is an important project sponsored by the China Ministry of Education, aiming to provide high-performance services in a Grid computing environment. In this paper, one of the applications offered by ChinaGrid, parallel remote-sensing image processing, is described. Geometric correction is a basic step during the processing of remote-sensing imagery, which is traditionally a computation-intensive and communication-intensive application if in parallel mode. In order to move this application into a Grid, a new Grid-enabled parallel algorithm of geometric correction is proposed, called GPGC. GPGC changes the frequent and fine-grain communication mode of the existing parallel method into a delayed but concentrated exchanging mode by computing an irregular local output area. This change means no communication or synchronization happens during resampling that occupies most of the execution time. To prove its efficiency, the complexity of GPGC is analyzed in theory. Finally, performance testing of GPGC and its application in ChinaGrid are given. Experimental results show that our algorithm is more suitable for a Grid platform, excelling the old method in both performance and salability.