Meaningful secret image sharing for JPEG images with arbitrary quality factors

Math Biosci Eng. 2022 Aug 11;19(11):11544-11562. doi: 10.3934/mbe.2022538.

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.

Keywords: JPEG images; meaningful shadows; quality factor; random elements utilization model; secret image sharing.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Data Compression* / methods
  • Humans
  • Image Processing, Computer-Assisted* / methods