On the use of morphological alternated sequential filters for the classification of remote sensing images from urban areas

Jocelyn Chanussot*, Jon Atli Benediktsson, Martino Pesaresi

*Corresponding author for this work

Research output: Contribution to conferencePaperpeer-review

8 Citations (Scopus)

Abstract

The problem of classification of high-resolution remotely sensed images from urban areas is addressed. Previous studies have shown the interest of exploiting the local geometrical information of each pixel to improve the classification. This is performed using the derivative morphological profile obtained with a granulometric approach using respectively opening and closing operators. We propose to replace this by a morphological alternated sequential filter, where the openings and the closings are applied alternately. The results and the robustness provided by the ASF are presented on IKONOS panchromatic data.

Original languageEnglish
Pages473-475
Number of pages3
Publication statusPublished - 2003
Event2003 IEEE IGARSS: Learning From Earth's Shapes and Colours - Toulouse, France
Duration: 21 Jul 200325 Jul 2003

Conference

Conference2003 IEEE IGARSS: Learning From Earth's Shapes and Colours
Country/TerritoryFrance
CityToulouse
Period21/07/0325/07/03

Other keywords

  • Alternated sequential filters
  • Classification
  • High resolution imagery
  • Mathematical morphology

Fingerprint

Dive into the research topics of 'On the use of morphological alternated sequential filters for the classification of remote sensing images from urban areas'. Together they form a unique fingerprint.

Cite this