Yan Bin, Xiang Yong, Hua Guang
IEEE Trans Image Process. 2018 Oct 8. doi: 10.1109/TIP.2018.2874378.
In visual cryptography (VC) for grayscale image, size reduction leads to bad perceptual quality to the reconstructed secret image. To improve the quality, the current efforts are limited to the design of VC algorithm for binary image, and measuring the quality with metrics that are not directly related to how the human visual system (HVS) perceives halftone images. We propose an analysis-by-synthesis (AbS) framework to integrate the halftoning process and the VC encoding: the secret pixel/block is reconstructed from the shares in the encoder and the error between the reconstructed secret and the original secret images is fed back and compensated concurrently by the error diffusion process. In doing so, the error between the reconstructed secret and original secret is pushed to high frequency band, thus producing visually pleasing reconstructed secret image. This framework is simple and flexible in that it can be combined with many existing size-invariant VC algorithms, including probabilistic VC, random grid VC and vector/block VC. More importantly, it is proved that this AbS framework is as secure as the traditional VC algorithms. Experimental results demonstrate the effectiveness of the proposed AbS framework.
在用于灰度图像的视觉密码术（VC）中，尺寸减小会导致重建的秘密图像的感知质量变差。为了提高质量，目前的努力仅限于设计用于二值图像的VC算法，并且使用与人类视觉系统（HVS）如何感知半色调图像没有直接关系的指标来衡量质量。我们提出了一种综合分析（AbS）框架，将半色调处理和VC编码集成在一起：在编码器中从共享图像重建秘密像素/块，并且重建的秘密图像与原始秘密图像之间的误差通过误差扩散过程同时反馈和补偿。这样，重建的秘密图像与原始秘密图像之间的误差被推到高频带，从而产生视觉上令人愉悦的重建秘密图像。该框架简单灵活，因为它可以与许多现有的尺寸不变VC算法相结合，包括概率VC、随机网格VC和矢量/块VC。更重要的是，证明了这种AbS框架与传统VC算法一样安全。实验结果证明了所提出的AbS框架的有效性。
