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Journal of Applied Remote Sensing

Hyperspectral image preprocessing with bilateral filter for improving the classification accuracy of support vector machines
Author(s): Anand S. Sahadevan; Aurobinda Routray; Bhabani S. Das; Saquib Ahmad
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Paper Abstract

Bilateral filter (BF) theory is applied to integrate spatial contextual information into the spectral domain for improving the accuracy of the support vector machine (SVM) classifier. The proposed classification framework is a two-stage process. First, an edge-preserved smoothing is carried out on a hyperspectral image (HSI). Then, the SVM multiclass classifier is applied on the smoothed HSI. One of the advantages of the BF-based implementation is that it considers the spatial as well as spectral closeness for smoothing the HSI. Therefore, the proposed method provides better smoothing in the homogeneous region and preserves the image details, which in turn improves the separability between the classes. The performance of the proposed method is tested using benchmark HSIs obtained from the airborne-visible-infrared-imaging-spectrometer (AVIRIS) and the reflective-optics-system-imaging-spectrometer (ROSIS) sensors. Experimental results demonstrate the effectiveness of the edge-preserved filtering in the classification of the HSI. Average accuracies (with 10% training samples) of the proposed classification framework are 99.04%, 98.11%, and 96.42% for AVIRIS–Salinas, ROSIS–Pavia University, and AVIRIS–Indian Pines images, respectively. Since the proposed method follows a combination of BF and the SVM formulations, it will be quite simple and practical to implement in real applications.

Paper Details

Date Published: 18 April 2016
PDF: 17 pages
J. Appl. Remote Sens. 10(2) 025004 doi: 10.1117/1.JRS.10.025004
Published in: Journal of Applied Remote Sensing Volume 10, Issue 2
Show Author Affiliations
Anand S. Sahadevan, Indian Institute of Technology Kharagpur (India)
Aurobinda Routray, Indian Institute of Technology Kharagpur (India)
Bhabani S. Das, Indian Institute of Technology Kharagpur (India)
Saquib Ahmad, Indian Institute of Technology Kharagpur (India)


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