Meaningful Secret Image Sharing with Uniform Image Quality

Autor: Jingwen Cheng, Lintao Liu, Feng Chen, Yue Jiang
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Mathematics, Vol 10, Iss 18, p 3241 (2022)
Druh dokumentu: article
ISSN: 2227-7390
DOI: 10.3390/math10183241
Popis: In meaningful secret image sharing (MSIS), a secret image is divided into n shadows. Each shadow is meaningful and similar to the corresponding cover image. Meaningful shadows can reduce the suspicion of attackers in transmission and facilitate shadow management. Previous MSIS schemes always include pixel expansion, and cross-interference from different shadows may exist when cover images are extremely unnatural images with large black and white blocks. In this article, we propose an MSIS with uniform image quality. A threshold t is set to determine the absolute salient regions. More identical bits are allocated according to saliency values in the absolute saliency region, which can improve image quality. In addition, the new identical bits allocation strategy also adjusts the randomness of the shadow images, generating shadows with uniform image quality and avoiding the cross-interference between different shadows. Experimental results show the effectiveness of our proposed scheme.
Databáze: Directory of Open Access Journals
Nepřihlášeným uživatelům se plný text nezobrazuje