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An Optimal Unsupervised Satellite Image Segmentation Approach Based On Pearson System And K-Means Clustering Algorithm Initialization
2009
Zenodo
This paper presents an optimal and unsupervised satellite image segmentation approach based on Pearson system and k-Means Clustering Algorithm Initialization. Such method could be considered as original by the fact that it utilised K-Means clustering algorithm for an optimal initialisation of image class number on one hand and it exploited Pearson system for an optimal statistical distributions- affectation of each considered class on the other hand. Satellite image exploitation requires the
doi:10.5281/zenodo.1085478
fatcat:d7fp2yxqcrd7vkfbkqvq3d622m