Estimation of the Number of Endmembers in Hyperspectral Images Using Agglomerative Clustering

Estimation of the Number of Endmembers in Hyperspectral Images Using Agglomerative Clustering

Many tasks in hyperspectral imaging, such as spectral unmixing and sub-pixel matching, require knowing how many substances or materials are present in the scene captured by a hyperspectral image. In this paper, we present an algorithm that estimates the number of materials in the scene using agglome...

Full description

Bibliographic Details
Main Authors: José Prades, Gonzalo Safont, Addisson Salazar, Luis Vergara
Format: Article
Language:English
Published: MDPI AG 2020-11-01
Series:Remote Sensing
Subjects:
agglomerative clustering
principal component analysis
model-based clustering
independent component analysis
Online Access:https://www.mdpi.com/2072-4292/12/21/3585

Internet

https://www.mdpi.com/2072-4292/12/21/3585

Similar Items