Semantic rich ICM algorithm for VHR satellite images segmentation

Author

Sublime, Jeremie ; Troya-Galvis, Andres ; Bennani, Younes ; Cornuejols, Antoine ; Gancarski, Pierre

Author_Institution

INRA, MIA, AgroParisTech, Paris, France

fYear

2015

fDate

18-22 May 2015

Firstpage

45

Lastpage

48

Abstract

In this article we show some applications of a MRF-based segmentation algorithm applied to real data extracted from a very high resolution image. This algorithm has specific features that enable the extraction of semantic information on the clusters in the form of affinity and geographic position properties. The results of the experiments conducted on this data set are interesting both in terms of clustering quality when using common unsupervised learning quality indexes, but also when compared to a ground-truth based on expert maps.

Keywords

Markov processes; image resolution; image segmentation; pattern clustering; MRF-based segmentation algorithm; Markov random field; VHR satellite image segmentation; clustering quality; expert map; geographic position property; iterated conditional mode; semantic information extraction; semantic rich ICM algorithm; unsupervised learning quality index; very high resolution image; Clustering algorithms; Data mining; Image resolution; Image segmentation; Indexes; Satellites; Semantics;

fLanguage

English

Publisher

ieee

Conference_Titel

Machine Vision Applications (MVA), 2015 14th IAPR International Conference on

Conference_Location

Tokyo

Type

conf

DOI

10.1109/MVA.2015.7153129

Filename

7153129