文章基本信息

标题：On Real-valued Visual Cryptographic Basis Matrices
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作者：Neil Buckley ; Atulya K. Nagar ; Subramanian Arumugam 等
期刊名称：Journal of Universal Computer Science
印刷版ISSN：0948-6968
出版年度：2015
卷号：21
期号：12
页码：1536-1562
出版社：Graz University of Technology and Know-Center
摘要：Visual cryptography (VC) encodes an image into noise-like shares, which can be stacked to reveal a reduced quality version of the original. The problem with encrypting colour images is that they must undergo heavy pre-processing to reduce them to binary, entailing significant quality loss. This paper proposes VC that works directly on intermediate grayscale values per colour channel and demonstrates real-valued basis matrices for this purpose. The resulting stacked shares produce a clearer reconstruction than in binary VC, and to the best of the authors' knowledge, is the first method posing no restrictions on colour values while maintaining the ability to decrypt with human vision. Grayscale and colour images of differing entropies are encrypted using fuzzy OR and XOR, and their PSNR and structural similarities are compared with binary VC to demonstrate improved quality. It is compared with previous research and its advantages highlighted, notably in high quality reconstructions with minimal processing.