@inproceedings{87934d5814584fc0a37b8ff2ec6a9079,
title = "Parallel optimization of geometric correction algorithm based on CPU-GPU hybrid architecture",
abstract = "Geometric correction is an essential processing procedure in remote sensing image processing. The algorithms used in geometric correction are time intensive and the size of remote sensing images is very large. Meanwhile, the data to be calculated is in huge size and is accumulating rapidly every day. Hence, the fast processing of geometric correction of remote sensing image becomes an urgent research problem. Through the rapid development of GPU, the current GPU has a great advantage in processing speed and memory bandwidth over CPU. It provides a new way for high performance computing. In this paper, we present three optimization solutions based on CPU-GPU hybrid architecture and the analysis of their performances. Experiments are also given and the results are consistent with the analysis.",
keywords = "GPU, Geometric correction, Parallel optimization, Remote sensing images",
author = "Bai, {Hong Tao} and Li, {Yu Gang} and Chen, {Li Ying} and Wang, {Yan Ling}",
year = "2014",
doi = "10.4028/www.scientific.net/AMM.543-547.2804",
language = "English",
isbn = "9783038350606",
series = "Applied Mechanics and Materials",
publisher = "Trans Tech Publications",
pages = "2804--2808",
booktitle = "Vehicle, Mechatronics and Information Technologies II",
address = "Germany",
note = "International Conference on Vehicle and Mechanical Engineering and Information Technology, VMEIT 2014 ; Conference date: 19-02-2014 Through 20-02-2014",
}