Analysis of Weighted Index for Segmentation Evaluation
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Abstract
The use of region based or object oriented techniques can enhance the accuracy of remote sensing based land cover
classifi cation. Due to the great amount of available segmenters and the need to select its parameters, a methodology
for segmentation evaluation and comparison is of great relevance. The Weighted Index for Segmentation Evaluation
(WISE) and some variations are analyzed in this work, by comparing them to other two indices from literature, for
optimal segmentation of synthetic images. The indices were also evaluated by the classifi cation results obtained with Neatest Neighbor classifi er. These indices were tested in three diff erent scenarios, that is, considering sets of
land cover classes with diff erent levels of separability. When compared to other indices, WISE and its variations
showed good results for segmentation selection, while some of the operational and theoretical problems found in
other indices were not observed.
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