Iterative learning control for image feature extraction with multiple-image blends

In this paper, a novel method of image extraction is proposed. Firstly, the image information is embedded into the parameters of the chaotic system, and then the image is overlapped and embedded to complete the image hiding. This process is equivalent to a dynamic system with unknown time-varying parameters. Secondly, the D-type iterative learning control algorithm is used to extract the information hidden in the image, because iterative learning can be used to estimate the time-varying parameter system completely in the time interval. Finally, the numerical simulation shows that the algorithm can effectively extract the hidden information under various attacks.