Confidential Image Super-Resolution with Privacy Protection

Nowadays, people are getting used to upload images to a third party for post-processing, such as image denoising and super-resolution. This may easily lead to the disclosure of the privacy in the confidential images. One possible solution is to encrypt the image before sending it to the third party, the encrypted image can be easily detected by a malicious attacker in the transmission channel. We propose a confidential image super-resolution method named HSR-Net which firstly hide the secret image and then super-resolve it in the hidden domain. The method is composed of three important modules: image hiding module (IHM), image super-resolution module (ISM), and image revealing module (IRM). The IHM aims to encode secret image and hide it into a cover image to generate the stego image. The stego image looks similar to the cover image but contains the information of the secret image. The third party uses the ISM to perform image super-resolution on the stego image. The user can reveal the super-resolved secret image from the stego image. The proposed HSR-Net method has two advantages. It ensures that the third party cannot directly operate on the secret image, thus protecting the user's privacy. Due to the similarity between the stego image and cover image, we can reduce the attacker's suspicion to further improve the image security. The experimental results were tested on DIV2K dataset and Flickr2K dataset. The peak signal-to-noise ratios (PSNR) of IHM, ISM, and IRM are 38.81 dB, 28.91 dB, and 23.51 dB, respectively, which verify that the proposed HSR-Net method is able to achieve image super-resolution and protect user's privacy simultaneouly.

Authors

Institutions

Publication Details

Journal
Chinese Journal of Electronics
Published
2024-11-01
DOI
https://doi.org/10.23919/cje.2023.00.034
Citations
5
Primary Topic
Advanced Image Processing Techniques
Type
article
Field-Weighted Citation Impact
1.25

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Confidential Image Super-Resolution with Privacy Protection

Yiran Han, Junpeng Jing, Xin Deng, Jianwei Liu et al.
5 citations
Chinese Journal of Electronics
Advanced Image Processing Techniques
1.25
article

Confidential Image Super-Resolution with Privacy Protection

Yiran Han, Junpeng Jing, Xin Deng, Jianwei Liu, Yanting Zhang
article en
5 citations

Abstract

Nowadays, people are getting used to upload images to a third party for post-processing, such as image denoising and super-resolution. This may easily lead to the disclosure of the privacy in the confidential images. One possible solution is to encrypt the image before sending it to the third party, the encrypted image can be easily detected by a malicious attacker in the transmission channel. We propose a confidential image super-resolution method named HSR-Net which firstly hide the secret image and then super-resolve it in the hidden domain. The method is composed of three important modules: image hiding module (IHM), image super-resolution module (ISM), and image revealing module (IRM). The IHM aims to encode secret image and hide it into a cover image to generate the stego image. The stego image looks similar to the cover image but contains the information of the secret image. The third party uses the ISM to perform image super-resolution on the stego image. The user can reveal the super-resolved secret image from the stego image. The proposed HSR-Net method has two advantages. It ensures that the third party cannot directly operate on the secret image, thus protecting the user's privacy. Due to the similarity between the stego image and cover image, we can reduce the attacker's suspicion to further improve the image security. The experimental results were tested on DIV2K dataset and Flickr2K dataset. The peak signal-to-noise ratios (PSNR) of IHM, ISM, and IRM are 38.81 dB, 28.91 dB, and 23.51 dB, respectively, which verify that the proposed HSR-Net method is able to achieve image super-resolution and protect user's privacy simultaneouly.

Chinese Journal of ElectronicsVol. 33(6)
China Electronics Standardization Institute (CN), Beihang University (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China, Fundamental Research Funds for the Central Universities, DOD Counterdrug Technology Development Program Office
Openalex Percentile: Top 18%
Advanced Image Processing Techniques
1.25
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.