Work

Rotation‐Invariant Saliency‐Guided Adaptive DWT‐Based Image Watermarking and Its Performance Across Various Extraction Methods

Year: 2026

Type: article

Abstract: ABSTRACT Blind image watermarking plays a major role in copyright protection and digital media authentication. Maintaining robustness against rotation attacks remains a challenging problem. This paper proposes a saliency‐guided adaptive watermarking framework based on discrete wavelet transform, with improved robustness against rotation. The proposed method employs a pre‐trained U 2 ‐Net heatmap to guide both adaptive subband selection and embedding strength. In adaptive subband selection, the primary embedding subband is selected from the gradient direction and watermark bits are then distributed across selected subbands using an alternating embedding. In addition, heatmap‐driven adaptive embedding strength is applied. For watermark extraction, the proposed framework integrates prediction‐based residual estimation and correlation‐based detection, with four extraction modes: prediction, weighted prediction, correlation and weighted detection. A rotation correction algorithm is introduced to counter rotation attacks. The algorithm evaluates candidate rotation angles and selects the optimal orientation based on the confidence score derived from detector responses. The proposed method is validated on standard test images and additional benchmark datasets under several attacks, including rotation, JPEG compression, scaling and noise perturbation. Empirical results show that the method maintains acceptable visual quality, with an average peak signal‐to‐noise ratio of 34.25 dB and a structural similarity index measure of 0.9951 and achieves robustness with a bit error rate of 0.0182 and a normalised correlation (NC) of 0.9635. These results indicate that the proposed method improves extraction robustness under rotation and JPEG compression, while the rotation correction process leads to additional computational cost.

Source: IET Image Processing

DOI: 10.1049/ipr2.70462

Authors: Paramate Horkaew, Jantana Panyavaraporn

Institutions: Suranaree University of Technology, Burapha University

Language: English

Topic: Advanced Steganography and Watermarking Techniques

Subfield: Computer Vision and Pattern Recognition

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $2,740

Funders: Burapha University, Thailand Science Research and Innovation