Hyperspectral Image Denoising via Correntropy-Based Nonconvex Low-Rank Approximation

Hyperspectral images (HSIs) are prone to be corrupted by various types of noise during the process of imaging and transmission, which seriously affect the subsequent HSI processing tasks. In this article, we proposed a novel low-rank-based model for HSIs denoising. On one hand, motivated by the supe...

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Autors principals:	Peizeng Lin, Lei Sun, Yaochen Wu, Weiyong Ruan
Format:	Artigo
Idioma:	Inglês
Publicat:	IEEE 2024-01-01
Col·lecció:	IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Matèries:	Correntropy hyperspectral image (HSI) denoising low-rank presentation nonconvex approximation
Accés en línia:	https://ieeexplore.ieee.org/document/10460099/
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