A data-distributed parallel algorithm for wavelet-based fusion of remote sensing images

被引：3

作者：

Yang X. ^{[1
]}

Wang P. ^{[1
]}

Du Y. ^{[1
]}

Zhou H. ^{[1
]}

机构：

[1] School of Computer, National University of Defense Technology

来源：

Frontiers of Computer Science in China | 2007年 / 1卷 / 02期

基金：

中国国家自然科学基金;

关键词：

Data distribution; Image fusion; Image registration; Load balancing; Redundant partitioning;

D O I：

10.1007/s11704-007-0024-1

中图分类号：

学科分类号：

摘要：

With the increasing importance of multiplatform remote sensing missions, the fast integration or fusion of digital images from disparate sources has become critical to the success of these endeavors. In this paper, to speed up the fusion process, a Data-distributed Parallel Algorithm for wavelet-based Fusion (DPAF for short) of remote sensing images which are not geo-registered remote sensing images is presented for the first time. To overcome the limitations on memory space as well as the computing capability of a single processor, data distribution, data-parallel processing and load balancing techniques are integrated into DPAF. To avoid the inherent communication overhead of a wavelet-based fusion method, a special design called redundant partitioning is used, which is inspired by the characteristics of wavelet transform. Finally, DPAF is evaluated in theory and tested on a 32-CPU cluster of workstations. The experimental results show that our algorithm has good parallel performance and scalability. © Higher Education Press 2007.

引用

页码：231 / 240

页数：9

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