Digital watermarking method based on heteroassociative image compression and its realization with artificial neural networks

In this paper, we present a digital watermarking method and associated algorithms that use a heteroassociative compressive transformation to embed a digital watermark bit sequence into blocks (fragments) of container images. A principal feature of the proposed method is the use of the heteroassociative compressing transformation - a mutual mapping with the compression of two neighboring image regions of an arbitrary shape. We also present the results of our experiments, namely the dependencies of quality indicators of thus created digital watermarks, which show the container distortion level, and the probability of digital watermark extraction error. In the final section, we analyze the performance of the proposed digital watermarking algorithms under various distortions and transformations aimed at destroying the hidden data, and compare these algorithms with the existing ones.