A comparison of self-dual attribute profiles based on different filter rules for classification

Gabriele Cavallaro, Mauro Dalla Mura, Jon Atli Benediktsson, Lorenzo Bruzzone

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper we compare features obtained by different filtering strategies for morphological attribute filters by considering non-increasing attributes. The Attribute profiles (APs) and Self Dual Attribute Profiles (SDAPs) are obtained by sequentially applying attribute filters on tree-based image representations, such as Min- or Max-trees and Inclusion tree, respectively. This work aims to study the effects of using the filtering rules max, min, direct and subtractive, when considering the non-increasing attributes moment of inertia and standard deviation. A very high spatial resolution data set is used in the experiments, and the extracted information obtained by the profiles is analyzed. This is done by studying the effects on the classification accuracy by using the profiles as additional input features to a Random Forest classifier

Original languageEnglish
Title of host publicationInternational Geoscience and Remote Sensing Symposium (IGARSS)
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1265-1268
Number of pages4
ISBN (Electronic)9781479957750
DOIs
Publication statusPublished - 4 Nov 2014
EventJoint 2014 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2014 and the 35th Canadian Symposium on Remote Sensing, CSRS 2014 - Quebec City, Canada
Duration: 13 Jul 201418 Jul 2014

Publication series

NameInternational Geoscience and Remote Sensing Symposium (IGARSS)

Conference

ConferenceJoint 2014 IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2014 and the 35th Canadian Symposium on Remote Sensing, CSRS 2014
Country/TerritoryCanada
CityQuebec City
Period13/07/1418/07/14

Bibliographical note

Publisher Copyright: © 2014 IEEE.

Other keywords

  • connected filters
  • image processing
  • mathematical morphology
  • tree representations

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