PM-LSMN: A Physical-Model-Based Lightweight Self-Attention Multiscale Net for Thin Cloud Removal-Reference-Cited by-同舟云学术

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PM-LSMN: A Physical-Model-Based Lightweight Self-Attention Multiscale Net for Thin Cloud Removal

Published:2024 Issue: Volume:21 Page:1-5
ISSN:1545-598X
Container-title:IEEE Geoscience and Remote Sensing Letters
language:
Short-container-title:IEEE Geosci. Remote Sensing Lett.

Author:

Zhao Bowen¹,Zhou Jianlin¹,Xu Hongxiang²,Feng Xiaoxing¹,Sun Yaxing³^ORCID

Affiliation:

1. School of Electronic Engineering and Optoelectronics Technology, Nanjing University of Science and Technology, Nanjing, China

2. School of Astronautics, Harbin Institute of Technology, Harbin, China

3. Engineering Training Center, Nanjing University of Science and Technology, Nanjing, China

Funder

National Undergraduate Training Program for Innovation and Entrepreneurship

Jiangsu Undergraduate Training Program for Innovation and Entrepreneurship

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/8859/10365397/10535981.pdf?arnumber=10535981

Reference15 articles.

1. Automatic Cloud Detection for All-Sky Images Using Superpixel Segmentation

2. Wavelet Integrated Convolutional Neural Network for Thin Cloud Removal in Remote Sensing Images

3. An effective thin cloud removal procedure for visible remote sensing images

4. Haze Removal for a Single Remote Sensing Image Based on Deformed Haze Imaging Model

5. An Effective Network Integrating Residual Learning and Channel Attention Mechanism for Thin Cloud Removal

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