Lightweight and Robust Hyperspectral Image Classification via Cyclic Heterogeneous MNF1-Guided Spectral-Band Filtering

Deep learning has become dominant in hyperspectral image classification owing to its strength in jointly exploiting spectral and spatial information. However, this requires long training times and substantial computational resources. Spectral inconsistency across adjacent bands is a persistent chall...

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Hlavní autoři:	Muhammad Shehzad Hanif, Muhammad Bilal, Saud Wasly
Médium:	Artigo
Jazyk:	Inglês
Vydáno:	IEEE 2026-01-01
Edice:	IEEE Access
Témata:	Minimum noise fraction principal component analysis hyperspectral channel denoising spectral-spatial preprocessing edge-preserving guided image filtering support vector machines
On-line přístup:	https://ieeexplore.ieee.org/document/11580328/
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