Mixed Noise Estimation Model for Optimized Kernel Minimum Noise Fraction Transformation in Hyperspectral Image Dimensionality Reduction

Mixed Noise Estimation Model for Optimized Kernel Minimum Noise Fraction Transformation in Hyperspectral Image Dimensionality Reduction

Dimensionality reduction (DR) is of great significance for simplifying and optimizing hyperspectral image (HSI) features. As a widely used DR method, kernel minimum noise fraction (KMNF) transformation preserves the high-order structures of the original data perfectly. However, the conventional KMNF...

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Bibliographic Details
Main Authors: Tianru Xue, Yueming Wang, Yuwei Chen, Jianxin Jia, Maoxing Wen, Ran Guo, Tianxiao Wu, Xuan Deng
Format: Article
Language:English
Published: MDPI AG 2021-07-01
Series:Remote Sensing
Subjects:
hyperspectral image (HSI)
dimensionality reduction (DR)
mixed noise estimation model (MNEM)
optimized KMNF (OP-KMNF)
graphics processing units (GPU)
Online Access:https://www.mdpi.com/2072-4292/13/13/2607

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