Truncated Robust Natural Watermarking With Hungarian Optimization
Truncated Robust Natural Watermarking With Hungarian Optimization is a scholarly work by Yuan-Gen Wang, Guopu Zhu, and Sam Kwong, published in 2022 in ''IEEE Transactions on Circuits and Systems for Video Technology''. The main subjects of the publication include biological robustness, steganography, digital forensics, computer science, algorithm, digital watermark, and embedding. The authors propose a new secure SS embedding method named truncated-RNW (TRNW), which improves the robustness of RNW while maintaining the same security level.