A new assessment measure of shadow image quality based on error diffusion techniques

A formal approach to study quality of shadow images in secret image sharing schemes based on error diffusion techniques is introduced. A novel secret sharing quality measure for assessment of shadow image quality, namely average flipping rate (AFR), that formulates and judges the visual quality of shadow images is proposed. This quality measure gives an indication about the quality of shadow images, that could be computed before sharing, with less complex computation overhead than the modified peak signal-tonoise ratio (MPSNR). Numerical analysis shows that the proposed quantitative technique has lower computation overhead and keeps in step with those taken by MPSNR. The new quality measure for assessment of shadow image quality will be useful for the development of secret image sharing techniques.