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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書誌詳細

出版年:	IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
主要な著者:	Peizeng Lin, Lei Sun, Yaochen Wu, Weiyong Ruan
フォーマット:	論文
言語:	英語
出版事項:	IEEE 2024-01-01
主題:	Correntropy hyperspectral image (HSI) denoising low-rank presentation nonconvex approximation
オンライン･アクセス:	https://ieeexplore.ieee.org/document/10460099/