PIRNet: Privacy-Preserving Image Restoration Network via Wavelet Lifting
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.
Code (0)
등록된 구현이 없습니다.
Tasks
DeblurringDenoisingImage DenoisingImage RestorationPrivacy PreservingSuper-ResolutionMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
Global Modeling Matters: A Fast, Lightweight and Effective Baseline for Efficient Image Restoration
Natural image quality is often degraded by adverse weather conditions, significantly impairing the performance of downstream tasks. Image restoration has emerged as a core solution to this challenge and has been widely d…
Image Super-ResolutionImage RestorationImage DehazingWaMaIR: Image Restoration via Multiscale Wavelet Convolutions and Mamba-based Channel Modeling with Texture Enhancement
Image restoration is a fundamental and challenging task in computer vision, where CNN-based frameworks demonstrate significant computational efficiency. However, previous CNN-based methods often face challenges in adequa…
Computational EfficiencyImage RestorationWavelet Frame Based Image Restoration Using Sparsity, Nonlocal and Support Prior of Frame Coefficients
The wavelet frame systems have been widely investigated and applied for image restoration and many other image processing problems over the past decades, attributing to their good capability of sparsely approximating pie…
Image RestorationWaveDM: Wavelet-Based Diffusion Models for Image Restoration
Latest diffusion-based methods for many image restoration tasks outperform traditional models, but they encounter the long-time inference problem. To tackle it, this paper proposes a Wavelet-Based Diffusion Model (WaveDM…
DeblurringDenoisingImage RestorationRaindrop Removal+1Image Restoration: A General Wavelet Frame Based Model and Its Asymptotic Analysis
Image restoration is one of the most important areas in imaging science. Mathematical tools have been widely used in image restoration, where wavelet frame based approach is one of the successful examples. In this paper,…
Image Restoration