{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,2]],"date-time":"2026-04-02T15:44:33Z","timestamp":1775144673435,"version":"3.50.1"},"reference-count":26,"publisher":"MDPI AG","issue":"15","license":[{"start":{"date-parts":[[2024,7,31]],"date-time":"2024-07-31T00:00:00Z","timestamp":1722384000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Young Elite Scientists Sponsorship Program of the CAST","award":["2023QNRC001"],"award-info":[{"award-number":["2023QNRC001"]}]},{"name":"Young Elite Scientists Sponsorship Program of the CAST","award":["2242024K30005"],"award-info":[{"award-number":["2242024K30005"]}]},{"name":"Young Elite Scientists Sponsorship Program of the CAST","award":["2242024RCB0023"],"award-info":[{"award-number":["2242024RCB0023"]}]},{"name":"Fundamental Research Funds for the Central Universities","award":["2023QNRC001"],"award-info":[{"award-number":["2023QNRC001"]}]},{"name":"Fundamental Research Funds for the Central Universities","award":["2242024K30005"],"award-info":[{"award-number":["2242024K30005"]}]},{"name":"Fundamental Research Funds for the Central Universities","award":["2242024RCB0023"],"award-info":[{"award-number":["2242024RCB0023"]}]},{"name":"Zhishan Youth Scholar Program of Southeast University","award":["2023QNRC001"],"award-info":[{"award-number":["2023QNRC001"]}]},{"name":"Zhishan Youth Scholar Program of Southeast University","award":["2242024K30005"],"award-info":[{"award-number":["2242024K30005"]}]},{"name":"Zhishan Youth Scholar Program of Southeast University","award":["2242024RCB0023"],"award-info":[{"award-number":["2242024RCB0023"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Given the propagation characteristics of sound waves and the complexity of the underwater environment, denoising forward-looking sonar image data presents a formidable challenge. Existing studies often add noise to sonar images and then explore methods for its removal. This approach neglects the inherent complex noise in sonar images, resulting in inaccurate evaluations of traditional denoising methods and poor learning of noise characteristics by deep learning models. To address the lack of high-quality data for FLS denoising model training, we propose a simulation algorithm for forward-looking sonar data based on RGBD data. By utilizing rendering techniques and noise simulation algorithms, high-quality noise-free and noisy sonar data can be rapidly generated from existing RGBD data. Based on these data, we optimize the loss function and training process of the FLS denoising model, achieving significant improvements in noise removal and feature preservation compared to other methods. Finally, this paper performs both qualitative and quantitative analyses of the algorithm\u2019s performance using real and simulated sonar data. Compared to the latest FLS denoising models based on traditional methods and deep learning techniques, our method demonstrates significant advantages in denoising capability. All inference results for the Marine Debris Dataset (MDD) have been made open source, facilitating subsequent research and comparison.<\/jats:p>","DOI":"10.3390\/rs16152815","type":"journal-article","created":{"date-parts":[[2024,7,31]],"date-time":"2024-07-31T17:16:49Z","timestamp":1722446209000},"page":"2815","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["SimNFND: A Forward-Looking Sonar Denoising Model Trained on Simulated Noise-Free and Noisy Data"],"prefix":"10.3390","volume":"16","author":[{"ORCID":"https:\/\/orcid.org\/0009-0003-9390-5756","authenticated-orcid":false,"given":"Taihong","family":"Yang","sequence":"first","affiliation":[{"name":"School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China"},{"name":"The Key Laboratory of Micro-Inertial Instrument and Advanced Navigation Technology, Ministry of Education, Nanjing 210096, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9955-3905","authenticated-orcid":false,"given":"Tao","family":"Zhang","sequence":"additional","affiliation":[{"name":"School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China"},{"name":"The Key Laboratory of Micro-Inertial Instrument and Advanced Navigation Technology, Ministry of Education, Nanjing 210096, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-5721-7129","authenticated-orcid":false,"given":"Yiqing","family":"Yao","sequence":"additional","affiliation":[{"name":"School of Instrument Science and Engineering, Southeast University, Nanjing 210096, China"},{"name":"The Key Laboratory of Micro-Inertial Instrument and Advanced Navigation Technology, Ministry of Education, Nanjing 210096, China"}]}],"member":"1968","published-online":{"date-parts":[[2024,7,31]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"250","DOI":"10.1016\/j.ecss.2018.04.017","article-title":"Side scan sonar: A cost-efficient alternative method for measuring seagrass cover in shallow environments","volume":"207","author":"Greene","year":"2018","journal-title":"Estuar. 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