Design and Storage Optimization of GPU-based Parallel Program of Image Registration for Remote Sensing

DOI

10.2991/icmt-13.2013.195How to use a DOI?

Keywords

GPU Mutual information Image registration Parallel algorithm.

Abstract

Image registration is a crucial step of many remote sensing related applications. As the scale of data and complexity of algorithm keep growing, image registration faces great challenges of its processing speed. In recent years, the computing capacity of GPU improves greatly. Taking the benefits of using GPU to solve general propose problem, we research on GPU-based remote sensing image registration algorithm. A mutual information based wavelet registration algorithm is proposed on the GPU parallel programming model, and storage optimization strategy is applied on the registration process. Using CUDA language, we tested our proposed methods with nVIDIA Tesla M2050 GPU. The experiment results prove that the parallel programming model and storage optimization strategy can well adapt to the field of remote sensing image registration, with a speedup of 19.9x. Our research also shows that the GPU-based general propose computing has a bright future in the field of remote sensing image processing.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Zhou Haifang
AU  - Xu Rulin
AU  - Jiang Jingfei
PY  - 2013/11
DA  - 2013/11
TI  - Design and Storage Optimization of GPU-based Parallel Program of Image Registration for Remote Sensing
BT  - Proceedings of 3rd International Conference on Multimedia Technology(ICMT-13)
PB  - Atlantis Press
SP  - 1597
EP  - 1605
SN  - 1951-6851
UR  - https://doi.org/10.2991/icmt-13.2013.195
DO  - 10.2991/icmt-13.2013.195
ID  - Haifang2013/11
ER  -