Open AccessA MINIMUM SPANNING TREE BASED METHOD FOR UAV IMAGE SEGMENTATION
Author(s) -
Ping Wang,
Zheng Wang,
Weihong Cui,
Lin Zhao
Publication year - 2016
Publication title -
isprs annals of the photogrammetry, remote sensing and spatial information sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.356
H-Index - 38
eISSN - 2194-9042
pISSN - 2196-6346
DOI - 10.5194/isprsannals-iii-7-111-2016
Subject(s) - segmentation , minimum spanning tree based segmentation , artificial intelligence , minimum spanning tree , image segmentation , computer science , scale space segmentation , computer vision , segmentation based object categorization , range segmentation , pattern recognition (psychology) , algorithm
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.