作者
M Jahanzeb Khan, Suman Rath, Muhammad Hassan Zaib
发表日期
2024/4/29
研讨会论文
2024 12th International Symposium on Digital Forensics and Security (ISDFS)
页码范围
1-6
出版商
IEEE
简介
This research addresses the dual challenges of image restoration quality and data privacy in optical remote sensing. Traditional restoration methods often fall short due to the complex nature of remote sensing images, and data privacy concerns further complicate the use of advanced techniques. By integrating the Deep Memory Connected Neural Network (DMCN) with the Data-Decoupled Federated Learning (DDFL) framework, our approach enables significant improvements in image restoration without requiring direct access to sensitive raw data. This method not only enhances data privacy by leveraging federated learning principles but also incorporates advanced techniques like Gaussian image denoising to maintain high restoration quality despite potential noise introduced by the federated process. The performance of the federated DMCN, particularly on the UCMERCED dataset, demonstrates minimal …
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MJ Khan, S Rath, MH Zaib - 2024 12th International Symposium on Digital …, 2024