Estimation of data hiding capacity of digital video based on human visual model in temporal domain

A new approach to evaluation of the data hiding capacity of digital video is presented in this paper. The paper reconsiders the conventional capacity estimation algorithms, in which the video signal is taken as a sequence of still images, that result in an exaggerated upper bound of hiding capacity or a much higher value than the actual embedding capacity. The proposed method for the capacity estimation is based on the human visual model in temporal domain, which leads to a more realistic, tighter bound for video capacity. In this method, according to temporal characteristic of every frame, a visibility based coefficient is extracted that is used to determine the hiding capacity. The maximum allowable distortion applied to each frame is modified by this coefficient, and then the frame capacity is computed through an information-theoretic approach.