Removal of Mixed Noise in Hyperspectral Images Based on Subspace Representation and Nonlocal Low-Rank Tensor Decomposition

Hyperspectral images (HSIs) contain abundant spectral and spatial structural information, but they are inevitably contaminated by a variety of noises during data reception and transmission, leading to image quality degradation and subsequent application hindrance. Hence, removing mixed noise from hy...

Täydet tiedot

Bibliografiset tiedot

Päätekijät:	Chun He, Youhua Wei, Ke Guo, Hongwei Han
Aineistotyyppi:	Artigo
Kieli:	Inglês
Julkaistu:	MDPI AG 2024-01-01
Sarja:	Sensors
Aiheet:	hyperspectral image mixed noise removal subspace representation low-rank tensor decomposition global spectral low-rank spatial nonlocal self-similarity
Linkit:	https://www.mdpi.com/1424-8220/24/2/327
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