DLR-Logo -> http://www.dlr.de
DLR Portal Home | Imprint | Privacy Policy | Contact | Deutsch
Fontsize: [-] Text [+]

Histogram correlation in the context of land cover classification from multi-polarized SAR data

Schmitt, Andreas (2015) Histogram correlation in the context of land cover classification from multi-polarized SAR data. In: IEEE International Geoscience and Remote Sensing Symposium, pp. 1-4. Intenational Geoscience and Remote Sensing Symposium, 26.-31. Juli 2015, Mailand, Italien.

[img] PDF - Registered users only


Land cover classification is a widely used application of remote sensing data. However, some very basic problems occur when the sophisticated approaches recently developed for the classification of optical remote sensing data are applied to SAR data. All problems can be referred to the “strange” statistical behavior of SAR data. For instance, the multiplicative noise contribution complicates the pixel-wise classification as even pixels belonging to the same class may differ greatly. Furthermore, even if the target shapes are given in advance, the standard classification algorithms often fail because a normal distribution of the underlying image data is required which is approximately true for optical data set, but completely wrong with view to SAR data. One way to adapt SAR data to the needs of these classification algorithms is the use of logarithmic intensities or normalized Kennaugh elements with respect to multi-polarized images. Alternatively, different classification algorithms could be utilized that are completely independent of the underlying distribution [1]. In this contribution, a classification approach based on histogram correlation (often used in Computer Vision) is studied. First, the distribution of training classes in terms of Kennaugh elements and Schmittlet indices is focused. Then, the classes are correlated in order to perform a basic separability analysis. Finally, the sample histograms are correlated with the whole image and the class of the best-fitting sample histogram is accepted for each pixel. Visual inspection underlines that this is a very simple, but remarkably sensitive approach. Numerical validation will follow soon.

Item URL in elib:https://elib.dlr.de/100096/
Document Type:Conference or Workshop Item (Poster)
Title:Histogram correlation in the context of land cover classification from multi-polarized SAR data
AuthorsInstitution or Email of AuthorsAuthors ORCID iD
Schmitt, AndreasAndreas.Schmitt (at) dlr.deUNSPECIFIED
Journal or Publication Title:IEEE International Geoscience and Remote Sensing Symposium
Refereed publication:No
Open Access:No
Gold Open Access:No
In ISI Web of Science:Yes
Page Range:pp. 1-4
Keywords:SAR, Classification, Histogram, Multi-Polarized, Land Cover
Event Title:Intenational Geoscience and Remote Sensing Symposium
Event Location:Mailand, Italien
Event Type:international Conference
Event Dates:26.-31. Juli 2015
HGF - Research field:Aeronautics, Space and Transport
HGF - Program:Space
HGF - Program Themes:Earth Observation
DLR - Research area:Raumfahrt
DLR - Program:R EO - Erdbeobachtung
DLR - Research theme (Project):R - Vorhaben Fernerkundung der Landoberfläche (old)
Location: Oberpfaffenhofen
Institutes and Institutions:German Remote Sensing Data Center > Land Surface
Deposited By: Schmitt, Andreas
Deposited On:07 Dec 2015 13:46
Last Modified:09 Feb 2017 19:21

Repository Staff Only: item control page

Help & Contact
electronic library is running on EPrints 3.3.12
Copyright © 2008-2017 German Aerospace Center (DLR). All rights reserved.