A new band selection framework for hyperspectral remote sensing image classification

A new band selection framework for hyperspectral remote sensing image classification

Abstract Dimensionality Reduction (DR) is an indispensable step to enhance classifier accuracy with data redundancy in hyperspectral images (HSI). This paper proposes a framework for DR that combines band selection (BS) and effective spatial features. The conventional clustering methods for BS typic...

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Bibliographic Details
Main Authors: B. L. N. Phaneendra Kumar, Radhesyam Vaddi, Prabukumar Manoharan, L. Agilandeeswari, V. Sangeetha
Format: Article
Language:English
Published: Nature Portfolio 2024-12-01
Series:Scientific Reports
Subjects:
Hyperspectral
PCA
Nonlinear
Smoothing filter-weighted least squares
Hyperbolic sigmoid
Spectral
Online Access:https://doi.org/10.1038/s41598-024-83118-8
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