Tensor Robust CUR for Compression and Denoising of Hyperspectral Data

Hyperspectral images are often contaminated with noise which degrades the quality of data. Recently, tensor robust principal component analysis (TRPCA) has been utilized to remove noise from hyperspectral images, improving classification accuracy. However, the high dimensionality and size of hypersp...

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מידע ביבליוגרפי

Principais autores:	Mohammad M. Salut, David V. Anderson
פורמט:	Artigo
שפה:	Inglês
יצא לאור:	IEEE 2023-01-01
סדרה:	IEEE Access
נושאים:	Low-rank tensor recovery tensor robust CUR tensor robust PCA hyperspectral image denoising noisy hyperspectral image classification
גישה מקוונת:	https://ieeexplore.ieee.org/document/10189858/
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