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Feature extraction based on extended multi-attribute profiles and sparse autoencoder for remote sensing image classification
Author(s): Hanane Teffahi; Hongxun Yao; Nasreddine Belabid; Souleyman Chaib
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Paper Abstract

The satellite images with very high spatial resolution have been recently widely used in image classification topic as it has become challenging task in remote sensing field. Due to a number of limitations such as the redundancy of features and the high dimensionality of the data, different classification methods have been proposed for remote sensing images classification particularly the methods using feature extraction techniques. This paper propose a simple efficient method exploiting the capability of extended multi-attribute profiles (EMAP) with sparse autoencoder (SAE) for remote sensing image classification. The proposed method is used to classify various remote sensing datasets including hyperspectral and multispectral images by extracting spatial and spectral features based on the combination of EMAP and SAE by linking them to kernel support vector machine (SVM) for classification. Experiments on new hyperspectral image "Huston data" and multispectral image "Washington DC data" shows that this new scheme can achieve better performance of feature learning than the primitive features, traditional classifiers and ordinary autoencoder and has huge potential to achieve higher accuracy for classification in short running time.

Paper Details

Date Published: 19 February 2018
PDF: 10 pages
Proc. SPIE 10607, MIPPR 2017: Multispectral Image Acquisition, Processing, and Analysis, 106070W (19 February 2018); doi: 10.1117/12.2288350
Show Author Affiliations
Hanane Teffahi, Harbin Institute of Technology (China)
Algerian Space Agency (Algeria)
Hongxun Yao, Harbin Institute of Technology (China)
Nasreddine Belabid, Algerian Space Agency (Algeria)
Beijing Univ. of Aeronautics and Astronautics (China)
Souleyman Chaib, Harbin Institute of Technology (China)
Algerian Space Agency (Algeria)

Published in SPIE Proceedings Vol. 10607:
MIPPR 2017: Multispectral Image Acquisition, Processing, and Analysis
Xinyu Zhang; Jun Zhang; Hongshi Sang, Editor(s)

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