Sparse Representing Denoising of Hyperspectral Data for Water Color Remote Sensing

Sparse Representing Denoising of Hyperspectral Data for Water Color Remote Sensing

Hyperspectral data are important for water color remote sensing. The inevitable noise will devalue its application. In this study, we developed a 1-D denoising method for water hyperspectral data, based on sparse representing. The denoising performance was compared with three commonly used methods i...

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Bibliographic Details
Main Authors: Yulong Guo, Qingsheng Bi, Yuan Li, Chenggong Du, Junchang Huang, Weiqiang Chen, Lingfei Shi, Guangxing Ji
Format: Article
Language:English
Published: MDPI AG 2022-07-01
Series:Applied Sciences
Subjects:
hyperspectral
denoising
water color remote sensing
sparse representing
bio-optical model
Online Access:https://www.mdpi.com/2076-3417/12/15/7501

Internet

https://www.mdpi.com/2076-3417/12/15/7501

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