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PIRNet: Privacy-Preserving Image Restoration Network via Wavelet Lifting

  • Beihang University

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

The cloud-based multimedia service becomes increasingly popular in the last decade, however, it poses a serious threat to the client's privacy. To address this issue, many methods utilized image encryption as a defense mechanism. However, the encrypted images look quite different from the natural images, making them vulnerable to attackers. In this paper, we propose a novel method namely PIRNet, which operates privacy-preserving image restoration in the steganographic domain. Compared to existing methods, our method offers significant advantages in terms of invisibility and security. Specifically, we first propose a wavelet Lifting-based Invertible Hiding (LIH) network to conceal the secret image into the stego image. Then, a Lifting-based Secure Restoration (LSR) network is utilized to perform image restoration in the steganographic domain. Since the secret image remains hidden throughout the whole image restoration process, the privacy of clients can be largely ensured. In addition, since the stego image looks visually the same as the cover image, the attackers can hardly discover it, which significantly improves the security. The experimental results on different datasets show the superiority of our PIRNet over the existing methods on various privacy-preserving image restoration tasks, including image denoising, deblurring and super-resolution.

源语言英语
主期刊名Proceedings - 2023 IEEE/CVF International Conference on Computer Vision, ICCV 2023
出版商Institute of Electrical and Electronics Engineers Inc.
22311-22320
页数10
ISBN(电子版)9798350307184
DOI
出版状态已出版 - 2023
活动2023 IEEE/CVF International Conference on Computer Vision, ICCV 2023 - Paris, 法国
期限: 2 10月 20236 10月 2023

出版系列

姓名Proceedings of the IEEE International Conference on Computer Vision
ISSN(印刷版)1550-5499

会议

会议2023 IEEE/CVF International Conference on Computer Vision, ICCV 2023
国家/地区法国
Paris
时期2/10/236/10/23

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