Feature Extraction of Hyperspectral Remote Sensing in Parallel Computing Research Based on GPU

Author

Zhongping, Tao ; Yaohua, Luo ; Ke, Guo ; Shibo, Zhao

Author_Institution

Inf. Technol. Centre, Chengdu Univ. of Technol., Chengdu, China

fYear

2012

fDate

17-19 Aug. 2012

Firstpage

570

Lastpage

573

Abstract

This paper introduces the basic modes of image parallel processing, and analyzes the parallel processing ability and stream program mode of GPU. At the same time, in view of the hyperspectral remote sensing data due to the large amount of data caused by the operational characteristics of a long time, we study feature extraction of hyperspectral remote sensing algorithms of parallel strategy, especially for the PCA parallel process based on GPU. At last, we conduct a system experiment on hyperspectral remote sensing images to prove the validity of this method.

Keywords

feature extraction; geophysical image processing; graphics processing units; parallel programming; principal component analysis; remote sensing; GPU; PCA parallel processing; feature extraction; graphics processing unit; hyperspectral remote sensing algorithm; hyperspectral remote sensing data; image parallel processing; parallel computing research; principal component analysis; program mode stream; Graphics processing unit; Hyperspectral imaging; Instruction sets; Parallel processing; Principal component analysis; GPU; PCA; feature extraction; hyperspectral remote sensing; parallel compute;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational and Information Sciences (ICCIS), 2012 Fourth International Conference on

Conference_Location

Chongqing

Print_ISBN

978-1-4673-2406-9

Type

conf

DOI

10.1109/ICCIS.2012.155

Filename

6300574