Improving the visual quality of random grid-based visual secret sharing

Pixel expansion and visual quality of the revealed secret image are two major concerns in visual secret sharing (VSS). Random grid (RG) is an alternative approach to solve the pixel expansion problem by making the share as big as the original secret image, at the expense of sacrificing the visual quality of the reconstructed secret image. In this paper, two algorithms, including a contrast-enhanced RG-based VSS and a void-and-cluster-based (VAC-based) post-processing, are introduced to improve the reconstructed image quality. Experimental results and theoretical analysis are provided, illustrating that competitive visual quality is obtained by combined use of the two proposed methods. (C) 2012 Elsevier B.V. All rights reserved.