ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences
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Articles | Volume III-7
https://doi.org/10.5194/isprs-annals-III-7-111-2016
https://doi.org/10.5194/isprs-annals-III-7-111-2016
07 Jun 2016
 | 07 Jun 2016

A MINIMUM SPANNING TREE BASED METHOD FOR UAV IMAGE SEGMENTATION

Ping Wang, Zheng Wei, Weihong Cui, and Zhiyong Lin

Keywords: Statistical Learning, Minimum Spanning Tree (MST), Image Segmentation Rule

Abstract. This paper proposes a Minimum Span Tree (MST) based image segmentation method for UAV images in coastal area. An edge weight based optimal criterion (merging predicate) is defined, which based on statistical learning theory (SLT). And we used a scale control parameter to control the segmentation scale. Experiments based on the high resolution UAV images in coastal area show that the proposed merging predicate can keep the integrity of the objects and prevent results from over segmentation. The segmentation results proves its efficiency in segmenting the rich texture images with good boundary of objects.