A Robust Reversible Data Hiding Algorithm Based on Polar Harmonic Fourier Moments

Bin Ma, Zhongquan Tao, Jian Xu, Chunpeng Wang, Jian Li, Liwei Zhang

Abstract: The Robust Reversible Data Hiding (RRDH) algorithm can recover both the secret data and the cover image entirely from an intact stego image, and can still restore the secret message comprehensively even if the stego image undergoes various attacks. While many current RRDH schemes possess a strong capability for resisting attacks, they often fail to withstand geometric deformation attacks such as rotation and scaling. In this paper, a new RRDH algorithm based on Polar Harmonic Fourier Moments (PHFMs) is presented to enhance its resistance to geometric transformation attacks. Firstly, leveraging the rotation invariance of PHFMs, a quantitation index modulation algorithm is designed to embed secret data into the coefficients of PHFMs. This approach achieves a high degree of anti-geometric transformation capability for the stego image while minimizing image distortion. Additionally, the differences between the original and restored image are employed as compensation information and embedded into the restored image. Moreover, a two-dimensional reversible data hiding scheme is adopted to embed the compensation information in order to minimize image distortion. The combination of PHFMs transformation and two-dimensional reversible data hiding enables the proposed RRDH algorithm to achieve high visual quality and strong resistance capability against geometric transformation attacks. Extensive experimental results demonstrate that the proposed RRDH algorithm outperforms other state-of-the-art techniques.