Heterogeneity Measure Based Segmentation performance Evaluation for Remote Sensing Image
Abstract
In order to evaluate segmentation quality of high resolution remote sensing image, an un-supervised
segmentatio N Evaluation method based on heterogeneity measure was proposed. Firstly, global variance and
Weighted Moran index were introduced to express the Intro-object and Inter-object Heterogenei Ty. Then The two
heterogeneity measure were normalized and summed to evaluate the whole of performance. Secondly, to evaluate
the local quality of image objects, a heterogeneity measure based on object variance and local Gear Y index was
presented. Finally, an experiment is carried out on a remote sensing which was segmented by Multi-esolution
segmentation method. and heterogeneity measure proposed in this paper is used to evaluate the segmentation
result. It shows that the heterogeneity measure can effectively evaluate the different scale segmentation results and
meanwhile C An identify regions which are over-segmented or under-segmented.
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