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Proceedings Paper

Joint spatial and spectral analysis for remote sensing image classification
Author(s): Linlin Shen; Sen Jia
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Paper Abstract

With the development of sensors, the spatial and spectral resolutions of remote sensing data are getting much higher, which presents new possibilities and challenges for pixel based material classification. When most of the methods available in literature extract features in spectrum domain for land material classification, the rich information contained in hyperspectral data is not fully used. As a result, the classification accuracies reported in literature are not satisfying. In this work, we aim to use joint spatial and spectral analysis technique to extract information about signal variances in space, spectrum and joint space-spectrum domain. The feature thus extracted can better represent the signal variances and can thus improve overall classification accuracy.

Paper Details

Date Published: 8 December 2011
PDF: 5 pages
Proc. SPIE 8002, MIPPR 2011: Multispectral Image Acquisition, Processing, and Analysis, 80021G (8 December 2011); doi: 10.1117/12.902037
Show Author Affiliations
Linlin Shen, Shenzhen Univ. (China)
Sen Jia, Shenzhen Univ. (China)


Published in SPIE Proceedings Vol. 8002:
MIPPR 2011: Multispectral Image Acquisition, Processing, and Analysis
Faxiong Zhang; Faxiong Zhang, Editor(s)

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