Steganography of Digital Watermark Based on Artificial Neural Networks in Image Communication and Intellectual Property Protection

摘要

In this paper, a novel steganography of digital watermark scheme which contains digital watermark embedding and extraction processes is proposed. The proposed scheme is based on an iterative process of Arnold scrambling transform which is controlled by secret key shared by copyright owner and authorized users, and the extension of morphological component analysis theory which utilizes morphological diversity as the kernel role in blind source separation. This scheme overcomes the problem of too narrow hidden data bandwidth in traditional LSB replacement or LSB matching schemes. Compared with classic JPEG steganography schemes, the proposed scheme has much higher embedding capacity and broader applicability scope. Images acquired in experiments and the analysis of experimental results both prove the effectiveness of proposed scheme. Objective quantitative results of the peak signal to noise ratio, structural similarity, and normalized correlation indices confirm its brilliant steganography capability as well as its fine robustness to different noise attacks through communication channel.