Dynamic Ensemble Selection Approach for Hyperspectral Image Classification With Joint Spectral and Spatial Information

Bharath Bhushan Damodaran 1 Rama Rao Nidamanuri 1 Yuliya Tarabalka 2, 3
1 IIST - Indian Institute of Space and Science Technology
2 AYIN - Models of spatio-temporal structure for high-resolution image processing
CRISAM - Inria Sophia Antipolis - Méditerranée
3 TITANE - Geometric Modeling of 3D Environments
CRISAM - Inria Sophia Antipolis - Méditerranée
Abstract : Accurate generation of a land cover map using hyperspectral data is an important application of remote sensing. Multiple classifier system (MCS) is an effective tool for hyperspec-tral image classification. However, most of the research in MCS addressed the problem of classifier combination, while the potential of selecting classifiers dynamically is least explored for hyper-spectral image classification. The goal of this paper is to assess the potential of dynamic classifier selection/dynamic ensemble selection (DCS/DES) for classification of hyperspectral images, which consists in selecting the best (subset of) optimal classifier(s) relative to each input pixel by exploiting the local information content of the image pixel. In order to have an accurate as well as com-putationally fast DCS/DES, we proposed a new DCS/DES framework based on extreme learning machine (ELM) regression and a new spectral–spatial classification model, which incorporates the spatial contextual information by using the Markov random field (MRF) with the proposed DES method. The proposed classification framework can be considered as a unified model to exploit the full spectral and spatial information. Classification experiments carried out on two different airborne hyperspectral images demonstrate that the proposed method yields a significant increase in the accuracy when compared to the state-of-the-art approaches.
Document type :
Journal articles
Complete list of metadatas

Cited literature [46 references]  Display  Hide  Download
https://hal.inria.fr/hal-01184338
Contributor : Yuliya Tarabalka <>
Submitted on : Friday, August 14, 2015 - 11:24:59 AM
Last modification on : Saturday, August 11, 2018 - 8:42:01 AM
Long-term archiving on : Sunday, November 15, 2015 - 10:56:24 AM

File

2015Damodaran.pdf
Files produced by the author(s)

Identifiers

Collections

INRIA | UNIV-COTEDAZUR

Citation

Bharath Bhushan Damodaran, Rama Rao Nidamanuri, Yuliya Tarabalka. Dynamic Ensemble Selection Approach for Hyperspectral Image Classification With Joint Spectral and Spatial Information. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, IEEE, 2015, 8 (6), pp.2405-2417. ⟨10.1109/JSTARS.2015.2407493⟩. ⟨hal-01184338⟩

Export

BibTeX TEI DC DCterms EndNote

Share

Metrics

Record views

438

Files downloads

578

Contact


archive-ouverte@inria.fr