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Spatial Filtering in DCT Domain-Based Frameworks for Hyperspectral Imagery Classification

The State Key Laboratory of Information Engineering in Surveying, Mapping, and Remote Sensing, Wuhan University, Wuhan 430079, China
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Remote Sens. 2019, 11(12), 1405; https://doi.org/10.3390/rs11121405
Received: 7 May 2019 / Revised: 10 June 2019 / Accepted: 11 June 2019 / Published: 13 June 2019
(This article belongs to the Special Issue Robust Multispectral/Hyperspectral Image Analysis and Classification)
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Abstract

In this article, we propose two effective frameworks for hyperspectral imagery classification based on spatial filtering in Discrete Cosine Transform (DCT) domain. In the proposed approaches, spectral DCT is performed on the hyperspectral image to obtain a spectral profile representation, where the most significant information in the transform domain is concentrated in a few low-frequency components. The high-frequency components that generally represent noisy data are further processed using a spatial filter to extract the remaining useful information. For the spatial filtering step, both two-dimensional DCT (2D-DCT) and two-dimensional adaptive Wiener filter (2D-AWF) are explored. After performing the spatial filter, an inverse spectral DCT is applied on all transformed bands including the filtered bands to obtain the final preprocessed hyperspectral data, which is subsequently fed into a linear Support Vector Machine (SVM) classifier. Experimental results using three hyperspectral datasets show that the proposed framework Cascade Spectral DCT Spatial Wiener Filter (CDCT-WF_SVM) outperforms several state-of-the-art methods in terms of classification accuracy, the sensitivity regarding different sizes of the training samples, and computational time. View Full-Text
Keywords: Spectral-spatial hyperspectral classification; discrete cosine transform; structural filtering; SVM; wiener filter; transform domain filtering Spectral-spatial hyperspectral classification; discrete cosine transform; structural filtering; SVM; wiener filter; transform domain filtering
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MDPI and ACS Style

Bazine, R.; Wu, H.; Boukhechba, K. Spatial Filtering in DCT Domain-Based Frameworks for Hyperspectral Imagery Classification. Remote Sens. 2019, 11, 1405.

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