Improving K-Nearest Neighbor Approaches for Density-Based Pixel Clustering in Hyperspectral Remote Sensing Images

Improving K-Nearest Neighbor Approaches for Density-Based Pixel Clustering in Hyperspectral Remote Sensing Images

We investigated nearest-neighbor density-based clustering for hyperspectral image analysis. Four existing techniques were considered that rely on a K-nearest neighbor (KNN) graph to estimate local density and to propagate labels through algorithm-specific labeling decisions. We first improved two of...

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Bibliographic Details
Main Authors: Claude Cariou, Steven Le Moan, Kacem Chehdi
Format: Article
Language:English
Published: MDPI AG 2020-11-01
Series:Remote Sensing
Subjects:
clustering methods
density estimation
nearest neighbor search
deterministic algorithm
unsupervised learning
Online Access:https://www.mdpi.com/2072-4292/12/22/3745

Internet

https://www.mdpi.com/2072-4292/12/22/3745

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