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Proceedings Paper

Parallel K-dimensional tree classification based on semi-matroid structure for remote sensing applications
Author(s): Yang-Lang Chang; Zhi-Ming Chen; Jin-Nan Liu; Lena Chang; Jyh Perng Fang
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Paper Abstract

Satellite remote sensing images can be interpreted to provide important information of large-scale natural resources, such as lands, oceans, mountains, rivers, forests and minerals for Earth observations. Recent advances of remote sensing technologies have improved the availability of satellite imagery in a wide range of applications including high dimensional remote sensing data sets (e.g. high spectral and high spatial resolution images). The information of high dimensional remote sensing images obtained by state-of-the-art sensor technologies can be identified more accurately than images acquired by conventional remote sensing techniques. However, due to its large volume of image data, it requires a huge amount of storages and computing time. In response, the computational complexity of data processing for high dimensional remote sensing data analysis will increase. Consequently, this paper proposes a novel classification algorithm based on semi-matroid structure, known as the parallel k-dimensional tree semi-matroid (PKTSM) classification, which adopts a new hybrid parallel approach to deal with high dimensional data sets. It is implemented by combining the message passing interface (MPI) library, the open multi-processing (OpenMP) application programming interface and the compute unified device architecture (CUDA) of graphics processing units (GPU) in a hybrid mode. The effectiveness of the proposed PKTSM is evaluated by using MODIS/ASTER airborne simulator (MASTER) images and airborne synthetic aperture radar (AIRSAR) images for land cover classification during the Pacrim II campaign. The experimental results demonstrated that the proposed hybrid PKTSM can significantly improve the performance in terms of both computational speed-up and classification accuracy.

Paper Details

Date Published: 24 August 2010
PDF: 8 pages
Proc. SPIE 7810, Satellite Data Compression, Communications, and Processing VI, 78100S (24 August 2010); doi: 10.1117/12.862715
Show Author Affiliations
Yang-Lang Chang, National Taipei Univ. of Technology (Taiwan)
Zhi-Ming Chen, National Taipei Univ. of Technology (Taiwan)
Jin-Nan Liu, National Taipei Univ. of Technology (Taiwan)
Lena Chang, National Taiwan Ocean Univ. (Taiwan)
Jyh Perng Fang, National Taipei Univ. of Technology (Taiwan)


Published in SPIE Proceedings Vol. 7810:
Satellite Data Compression, Communications, and Processing VI
Bormin Huang; Antonio J. Plaza; Joan Serra-Sagristà; Chulhee Lee; Yunsong Li; Shen-En Qian, Editor(s)

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