Image patch characterization with shape distributions: Application to WorldView-2 images

Author

Gueguen, Lionel

Author_Institution

R&D Dept., DigitalGlobe Inc., Longmont, CO, USA

fYear

2013

fDate

21-26 July 2013

Firstpage

4387

Lastpage

4390

Abstract

This paper describes an image patch characterization for image information mining tasks. An image patch is first decomposed into a multi-scale segmentation thanks to the Max Tree representation. Then, each segment is described by shift invariant shape attributes. Finally, the segment attributes are aggregated into a shape distribution which constitutes the patch characterization. Illustrations of this image content description are given for patches of a WorldView-2 multi-spectral scene, and the information relevance is assessed by an automatic classification of the patch characteristics which is compared to land use/land cover annotations.

Keywords

data mining; geophysical image processing; image classification; image segmentation; land cover; land use; natural scenes; tree data structures; Max Tree representation; WorldView-2 images; WorldView-2 multispectral scene; automatic classification; image content description; image information mining tasks; image patch characterization; land use/land cover annotations; multiscale segmentation; shape distribution; shift invariant shape attributes; Image segmentation; Level set; Remote sensing; Semantics; Shape; Vegetation; Visualization;

fLanguage

English

Publisher

ieee

Conference_Titel

Geoscience and Remote Sensing Symposium (IGARSS), 2013 IEEE International

Conference_Location

Melbourne, VIC

ISSN

2153-6996

Print_ISBN

978-1-4799-1114-1

Type

conf

DOI

10.1109/IGARSS.2013.6723807

Filename

6723807