NDLI: Classification of Remote Sensing Optical and LiDAR Data Using Extended Attribute Profiles

Content Provider	IEEE Xplore Digital Library
Author	Pedergnana, M. Marpu, P.R. Dalla Mura, M. Benediktsson, J.A. Bruzzone, L.
Copyright Year	2007
Abstract	Extended Attribute Profiles (EAPs), which are obtained by applying morphological attribute filters to an image in a multilevel architecture, can be used for the characterization of the spatial characteristics of objects in a scene. EAPs have proved to be discriminant features when considered for thematic classification in remote sensing applications especially when dealing with very high resolution images. Altimeter data (such as LiDAR) can provide important information, which being complementary to the spectral one can be valuable for a better characterization of the surveyed scene. In this paper, we propose a technique performing a classification of the features extracted with EAPs computed on both optical and LiDAR images, leading to a fusion of the spectral, spatial and elevation data. The experiments were carried out on LiDAR data along either with a hyperspectral and a multispectral image acquired on a rural and urban area of the city of Trento (Italy), respectively. The classification accuracies obtained pointed out the effectiveness of the features extracted by EAPs on both optical and LiDAR data for classification.
Sponsorship	IEEE Signal Processing Society
Starting Page	856
Ending Page	865
Page Count	10
File Size	3221375
File Format	PDF
ISSN	19324553
Volume Number	6
Issue Number	7
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-11-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Laser radar Optical imaging Feature extraction Hyperspectral imaging Optical sensors Vegetation multispectral images Attribute filters classification extended attribute profiles hyperspectral images LiDAR
Content Type	Text
Resource Type	Article
Subject	Signal Processing Electrical and Electronic Engineering

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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