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Segmentation of High Resolution Worldview-2 Satellite Images

Authors: Shashidhar Sonnad; Lalitha Y. S.;

Segmentation of High Resolution Worldview-2 Satellite Images

Abstract

This paper presents the segmentation technique used to segment the Worldview-2 high resolution satellite multispectral (MS) images. First the spectral features like Simple Ratio (SR), Normalized Difference Vegetation Index (NDVI), Soil Adjusted Vegetation Index (SAVI) and Modified Soil Adjusted Vegetation Index (MSAVI) are considered to extract the spectral features from the MS image. Next the MS image is segmented by using the over segmented k-means algorithm with novel initialization (OSKNI) method. The proposed method performs well in terms of User’s accuracy (UA), Producer’s accuracy (PA) and overall segmentation accuracy (OVA) compared to the existing k-means algorithm.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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