Semantic Rich ICM Algorithm for VHR Satellite Images Segmentation

被引：0

作者：

Sublime, Jeremie ^{[1
,3
]}

Troya-Galvis, Andres ^{[2
]}

Bennani, Younes ^{[3
]}

Cornuejols, Antoine ^{[1
]}

Gancarski, Pierre ^{[2
]}

机构：

[1] AgroParisTech, UMR INRA MIA 518, 16 Rue Claude Bernard, F-75231 Paris 5, France

[2] Univ Strasbourg, ICube UMR CNRS 7357, F-67412 Illkirch Graffenstaden, France

[3] Univ Paris 13, LIPN UMR CNRS 7030, F-93430 Villetaneuse, France

来源：

2015 14TH IAPR INTERNATIONAL CONFERENCE ON MACHINE VISION APPLICATIONS (MVA) | 2015年

关键词：

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

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.

引用

页码：45 / 48

页数：4

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