A spatial-spectral adaptive thin-cloud removal method based on slow feature analysis-Reference-Cited by-同舟云学术

A spatial-spectral adaptive thin-cloud removal method based on slow feature analysis

Published:2022-05-31 Issue:8 Volume:13 Page:747-755
ISSN:2150-704X
Container-title:Remote Sensing Letters
language:en
Short-container-title:Remote Sensing Letters

Author:

Luo Xiaobo¹²³,Rong Wentao¹³,Zhou Jianjun¹³

Affiliation:

1. Institute of Computer Science and Technology, Chongqing University of Posts and Telecommunications, Chongqing, China

2. Chongqing Institute of Meteorological Sciences, Chongqing, China

3. Chongqing Engineering Research Center for Spatial Big Data Intelligent Technology, Chongqing University of Posts and Telecommunications, Chongqing, China

Funder

the National Natural Science Foundation of China

Publisher

Informa UK Limited

Subject

Electrical and Electronic Engineering,Earth and Planetary Sciences (miscellaneous)

Link

https://www.tandfonline.com/doi/pdf/10.1080/2150704X.2022.2079387

Reference14 articles.

1. Cloud removal for remotely sensed images by similar pixel replacement guided with a spatio-temporal MRF model

2. Multisensor Data Fusion for Cloud Removal in Global and All-Season Sentinel-2 Imagery

3. Using Slow Feature Analysis and a Cloud-Free Auxiliary Image to Remove Thin Clouds in Landsat-5 VINIR Band Data

4. An empirical and radiative transfer model based algorithm to remove thin clouds in visible bands

5. Missing Information Reconstruction of Remote Sensing Data: A Technical Review

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