Lattice-Aided Extraction of Spread-Spectrum Hidden Data

This paper delves into the challenges of spread spectrum (SS) watermarking extraction, considering both reference-free and referential extraction scenarios, within the framework of lattice decoding. The orthogonality of carriers plays a crucial role in the accuracy of extraction, impacting the bit error rate (BER). When carriers lack sufficient orthogonality, conventional reference-free extraction methods such as multi-carrier iterative generalized least-squares (M-IGLS) and referential extraction techniques like MMSE-based schemes encounter performance degradation, posing difficulties in accurately recovering hidden data at the receiver end. To address these challenges, we propose two novel SS watermarking extraction approaches by integrating precise lattice decoding algorithms. Firstly, we introduce the highly accurate yet computationally efficient successive interference cancellation (SIC) algorithm to augment M-IGLS, resulting in a new method termed multi-carrier iterative successive interference cancellation (M-ISIC). Secondly, we adapt the near-optimal sphere decoding (SD) technique for referential extraction in SS watermarking. Theoretical analysis and experimental simulations showcase that our proposed M-ISIC and SD methods outperform M-IGLS and MMSE-based detectors, particularly in scenarios where carrier orthogonality is limited, achieving lower BER. Our code is available at
https://github.com/shx-lyu/M_ISIC
.