Edge-Preserved Low-Rank Representation via Multi-Level Knowledge Incorporation for Remote Sensing Image Denoising

Edge-Preserved Low-Rank Representation via Multi-Level Knowledge Incorporation for Remote Sensing Image Denoising

The low-rank models have gained remarkable performance in the field of remote sensing image denoising. Nonetheless, the existing low-rank-based methods view residues as noise and simply discard them. This causes denoised results to lose many important details, especially the edges. In this paper, we...

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Bibliographic Details
Main Authors: Xiaolin Feng, Sirui Tian, Stanley Ebhohimhen Abhadiomhen, Zhiyong Xu, Xiangjun Shen, Jing Wang, Xinming Zhang, Wenyun Gao, Hong Zhang, Chao Wang
Format: Article
Language:English
Published: MDPI AG 2023-04-01
Series:Remote Sensing
Subjects:
low-rank representation
multi-level
remote sensing image
image denoising
edge preservation
Online Access:https://www.mdpi.com/2072-4292/15/9/2318

Internet

https://www.mdpi.com/2072-4292/15/9/2318

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