NN-based embedment of watermark in end-to-end image compression
EunSeong Lee, Jong‐Seok Lee, Young-Ho Seo, Donggyu Sim · 2023
This paper proposes a method of embedding and extracting watermark in end-to-end (E2E) image compression that is an emerging image compression framework. Although end-to-end image compression algorithms are recently developed based on deep neural networks to beat the conventional image compression methods, there are no research to support watermarking embedment and extraction for contents protections. This paper proposes a NN-based watermarking algorithm for end-to-end image coding. At the end-to-end image coder and decoder, the GDN-based multi-layer modules for embedment and extraction of watermark are equipped to support watermarking for E2E image compressor. The proposed method shows an average BD-rate gain of 8.07%, over the method of directly connecting the existing watermarking network and end-to-end image compression network. In addition, bit error rate (BER) of watermark is also improved by more than 2.7% in terms of robustness.