A Clustering Based Method for Edge Detection in Hyperspectral Images

Authors:
V. C. Dinh;Raimund Leitner;Pavel Paclik;Robert P. Duin
Affiliations:
ICT Group, Delft University of Technology, Delft, The Netherlands and Carinthian Tech Research AG, Villach, Austria;Carinthian Tech Research AG, Villach, Austria;PR Sys Design, Delft, The Netherlands;ICT Group, Delft University of Technology, Delft, The Netherlands
Venue:
SCIA '09 Proceedings of the 16th Scandinavian Conference on Image Analysis
Year:
2009

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Abstract

Edge detection in hyperspectral images is an intrinsically difficult problem as the gray value intensity images related to single spectral bands may show different edges. The few existing approaches are either based on a straight forward combining of these individual edge images, or on finding the outliers in a region segmentation. As an alternative, we propose a clustering of all image pixels in a feature space constructed by the spatial gradients in the spectral bands. An initial comparative study shows the differences and properties of these approaches and makes clear that the proposal has interesting properties that should be studied further.