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Land Classification using a novel Multispectral and SAR data Fusion in Doha area

Iervolino, Pasquale, Guida, Raffaella and Ayesh-Meagher, A (2018) Land Classification using a novel Multispectral and SAR data Fusion in Doha area In: 12th European Conference on Synthetic Aperture Radar (EUSAR 2018), 4 - 7 June 2018, Aachen, Germany..

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Abstract

A new algorithm for land classification is presented in this paper and is based on the fusion of Multispectral, Panchromatic and Synthetic Aperture Radar (SAR) images. The novel approach relies on Generalized Intensity-Hue-Saturation (G-HIS) transform and the Wavelet Transform (WT). The fused image is derived by modulating the SAR texture with the high features details of the Panchromatic WT and by injecting this product at the place of G-HIS high feature details. Finally, a classification is performed on the fused product by using a Maximum Likelihood (ML) classifier. The algorithm has been tested on data acquired by Sentinel-1 (SAR) and Landsat-8 (Multispectral and Panchromatic) over the area of Greater Doha in Qatar in 2017. Results show an increment of 3% in the overall accuracy for the fused product compared to the Multispectral dataset.

Item Type: Conference or Workshop Item (Conference Paper)
Divisions : Faculty of Engineering and Physical Sciences > Electronic Engineering
Authors :
NameEmailORCID
Iervolino, Pasqualep.iervolino@surrey.ac.uk
Guida, RaffaellaR.Guida@surrey.ac.uk
Ayesh-Meagher, A
Date : 2018
Copyright Disclaimer : Copyright 2018 VDE VERLAG GMBH
Depositing User : Melanie Hughes
Date Deposited : 12 Jun 2018 17:03
Last Modified : 16 Jan 2019 19:11
URI: http://epubs.surrey.ac.uk/id/eprint/847041

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