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SiGRRW: A Single-Watermark Robust Reversible Watermarking Framework with Guiding Strategy

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Robust reversible watermarking (RRW) enables copyright protection for images while overcoming the limitation of distortion introduced by watermark itself. Current RRW schemes typically employ a two-stage framework, which fails to achieve simultaneous robustness and reversibility within a single watermarking, and functional interference between the two watermarks results in performance degradation in multiple terms such as capacity and imperceptibility. We propose SiGRRW, a single-watermark RRW framework, which is applicable to both generative models and natural images. We introduce a novel guiding strategy to generate guiding images, serving as the guidance for embedding and recovery. The watermark is reversibly embedded with the guiding residual, which can be calculated from both cover images and watermark images. The proposed framework can be deployed either as a plug-and-play watermarking layer at the output stage of generative models, or directly applied to natural images. Extensive experiments demonstrate that SiGRRW effectively enhances imperceptibility and robustness compared to existing RRW schemes while maintaining lossless recovery of cover images, with significantly higher capacity than conventional schemes.

Zikai Xu, Bin Liu, Weihai Li, Lijunxian Zhang, Nenghai Yu• 2026

Related benchmarks

TaskDatasetResultRank
Robust and Reversible Watermarking256 x 256 color cover images unseen (val)
PSNR44.25
9
Watermark ExtractionCommon Distortions Benchmark
Accuracy (Gaussian Noise)100
5
Watermark ExtractionVAE-based Regeneration Attacks (Regen-VAE-Bmshj and Regen-VAE-Cheng)
BER (Regen-Bmshj, Q4)0.0455
2
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