Missing Data Reconstruction for Remote Sensing Images With Weighted Low-Rank Tensor Model

Missing Data Reconstruction for Remote Sensing Images With Weighted Low-Rank Tensor Model

Missing data reconstruction for remote sensing images, such as dead-pixel recovery and cloud removal, is important for remote sensing data applications. Missing information reconstruction is well known as being an ill-posed inverse problem. In this paper, a weighted low-rank tensor regularization mo...

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Bibliographic Details
Main Authors: Qing Cheng, Qiangqiang Yuan, Michael Kwok-Po Ng, Huanfeng Shen, Liangpei Zhang
Format: Article
Language:English
Published: IEEE 2019-01-01
Series:IEEE Access
Subjects:
Missing information reconstruction
tensor completion
low-rank model
remote sensing
Online Access:https://ieeexplore.ieee.org/document/8852746/

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