By Topic

Potential problems with using reconstruction in morphological profiles for classification of remote sensing images from urban areas

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

5 Author(s)
Bellens, R. ; Ghent Univ. - TELIN - IPI - IBBT, Ghent ; Martinez-Fonte, L. ; Sidharta Gautama ; Chan, J.C.
more authors

Meter to sub-meter resolution satellite images have generated new interests in extracting man-made structures in the urban area. However, classification accuracies for such purposes are far from satisfactory. Spectral characteristics of urban land cover classes are so similar that they cannot be separated using only spectral information. As a result, there is an increased interest in incorporating geometrical information. One possible approach is the use of a morphological profile [1]. This profile contains information about the size of objects. In literature this is usually combined with morphological reconstruction to better preserve the shapes of objects. In this paper, we show that when used for remote sensing images this leads to 'over- reconstruction', with a decreased classification performance as a result. We propose a new method called 'partial reconstruction' to overcome this problem and still be able to preserve the shape of objects. Classification experiments show a better performance with partial reconstruction.

Published in:

Geoscience and Remote Sensing Symposium, 2007. IGARSS 2007. IEEE International

Date of Conference:

23-28 July 2007