Meaningful secret image sharing for JPEG images with arbitrary quality factors

Yue Jiang; Xuehu Yan; Jia Chen; Jingwen Cheng; Jianguo Zhang; Yue Jiang; Xuehu Yan; Jia Chen; Jingwen Cheng; Jianguo Zhang

doi:10.3934/mbe.2022538

Mathematical Biosciences and Engineering

2022, Volume 19, Issue 11: 11544-11562. doi: 10.3934/mbe.2022538

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Research article

Meaningful secret image sharing for JPEG images with arbitrary quality factors

1.
National University of Defense Technology, Hefei 230037, China
2.
Anhui Province Key Laboratory of Cyberspace Security Situation Awareness and Evaluation, Hefei 230037, China
3.
INFOINNO Information Scurity Evaluation CO., LTD, Hefei 230022, China

Academic Editor: Runzhang Xu

Received: 29 April 2022 Revised: 13 July 2022 Accepted: 03 August 2022 Published: 11 August 2022

JPEG is the most common format for storing and transmitting photographic images on social network platforms. JPEG image is widely used in people's life because of their low storage space and high visual quality. Secret image sharing (SIS) technology is important to protect image data. Traditional SIS schemes generally focus on spatial images, however there is little research on frequency domain images. In addition, the current tiny research on SIS for JPEG images only focuses on JPEG images with a compression quality factor ($ QF $) of $ 100 $. To overcome the limitation of JPEG images in SIS, we propose a meaningful SIS for JPEG images to operate the quantized DCT coefficients of JPEG images. The random elements utilization model is applied to achieve meaningful shadow images. Our proposed scheme has a better quality of the shadow images and the recovered secret image. Experiment results and comparisons indicate the effectiveness of the scheme. The scheme can be used for JPEG images with any compression $ QF $. Besides, the scheme has good characteristics, such as $ (k, n) $ threshold, extended shadow images.
- secret image sharing,
- JPEG images,
- quality factor,
- random elements utilization model,
- meaningful shadows
Citation: Yue Jiang, Xuehu Yan, Jia Chen, Jingwen Cheng, Jianguo Zhang. Meaningful secret image sharing for JPEG images with arbitrary quality factors[J]. Mathematical Biosciences and Engineering, 2022, 19(11): 11544-11562. doi: 10.3934/mbe.2022538

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Abstract

JPEG is the most common format for storing and transmitting photographic images on social network platforms. JPEG image is widely used in people's life because of their low storage space and high visual quality. Secret image sharing (SIS) technology is important to protect image data. Traditional SIS schemes generally focus on spatial images, however there is little research on frequency domain images. In addition, the current tiny research on SIS for JPEG images only focuses on JPEG images with a compression quality factor ($ QF $) of $ 100 $. To overcome the limitation of JPEG images in SIS, we propose a meaningful SIS for JPEG images to operate the quantized DCT coefficients of JPEG images. The random elements utilization model is applied to achieve meaningful shadow images. Our proposed scheme has a better quality of the shadow images and the recovered secret image. Experiment results and comparisons indicate the effectiveness of the scheme. The scheme can be used for JPEG images with any compression $ QF $. Besides, the scheme has good characteristics, such as $ (k, n) $ threshold, extended shadow images.

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