Spatial-Aware Collaborative Representation For Hyperspectral Remote Sensing Image Classification

Keywords

Collaborative representation (CR); hyperspectral image (HSI) classification; spatial regularization; spectral spatial information

Abstract

Representation-residual-based classifiers have attracted much attention in recent years in hyperspectral image (HSI) classification. How to obtain the optimal representa-Tion coefficients for the classification task is the key problem of these methods. In this letter, spatial-Aware collaborative representation (CR) is proposed for HSI classification. In order to make full use of the spatial-spectral information, we propose a closed-form solution, in which the spatial and spectral features are both utilized to induce the distance-weighted regularization terms. Different from traditional CR-based HSI classification algorithms, which model the spatial feature in a preprocessing or postprocessing stage, we directly incorporate the spatial information by adding a spatial regularization term to the representation objective function. The experimental results on three HSI data sets verify that our proposed approach outperforms the state-of-The-Art classifiers.

Publication Date

3-1-2017

Publication Title

IEEE Geoscience and Remote Sensing Letters

Volume

14

Issue

3

Number of Pages

404-408

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1109/LGRS.2016.2645708

Socpus ID

85009966994 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85009966994

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