Segmentation-Guided Semantic-Aware Self-Supervised Denoising for SAR Image-Reference-Cited by-同舟云学术

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Segmentation-Guided Semantic-Aware Self-Supervised Denoising for SAR Image

Published:2023 Issue: Volume:61 Page:1-16
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Yuan Ye¹^ORCID,Wu Yanxia¹,Feng Pengming²^ORCID,Fu Yan¹^ORCID,Wu Yulei³^ORCID

Affiliation:

1. College of Computer Science and Technology, Harbin Engineering University, Harbin, China

2. State Key Laboratory of Space-Ground Integrated Information Technology, China Aerospace Science and Technology Corporation, Beijing, China

3. Faculty of Science and Engineering, University of Bristol, Bristol, U.K.

Funder

Fundamental Research Funds for the Central Universities

Natural Science Foundation of Heilongjiang Province

Fundamental Research Funds for the Central Universities–Research and Innovation Fund for Doctoral Students

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/36/10006360/10285521.pdf?arnumber=10285521

Reference46 articles.

1. A Novel Statistical Texture Feature for SAR Building Damage Assessment in Different Polarization Modes

2. Dense Attention Pyramid Networks for Multi-Scale Ship Detection in SAR Images

3. Change Detection in Synthetic Aperture Radar Images Based on Deep Neural Networks

4. A Tutorial on Speckle Reduction in Synthetic Aperture Radar Images

5. Wavelet-Based Despeckling of SAR Images Using Gauss–Markov Random Fields

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. DBW-YOLO: A High-Precision SAR Ship Detection Method for Complex Environments;IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing;2024

2. Wake2Wake: Feature-Guided Self-Supervised Wave Suppression Method for SAR Ship Wake Detection;IEEE Transactions on Geoscience and Remote Sensing;2024

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