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<p>Data storage and authentication present significant challenges in resource-constrained environments. This paper introduces a compressed domain robust image watermarking framework (CDRIWF) for digital images, employing Adaptive Inter-coefficient Difference (AID) and autoencoders. CDRIWF addresses storage efficiency and data authenticity by compressing images and embedding watermarks using Integer Lifting Wavelet Transform (ILWT) and AID. Our method achieves a compression ratio of 4, removing up to 75% redundancy, and demonstrates high robustness against various attacks. Experimental results show structural similarity index metric values near unity, peak signal-to-noise ratios above 41&#xa0;dB, and strong resilience to both singular and hybrid attacks, making it suitable for resource-constrained applications.</p>

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Robust image watermarking in compressed domain: a framework for digital image authentication

  • 期刊论文

  • 发表日期：

    2026年7月21日

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  • Samrah Mehraj,
  • Subreena Mushtaq,
  • Shabir A. Parah

摘要

Data storage and authentication present significant challenges in resource-constrained environments. This paper introduces a compressed domain robust image watermarking framework (CDRIWF) for digital images, employing Adaptive Inter-coefficient Difference (AID) and autoencoders. CDRIWF addresses storage efficiency and data authenticity by compressing images and embedding watermarks using Integer Lifting Wavelet Transform (ILWT) and AID. Our method achieves a compression ratio of 4, removing up to 75% redundancy, and demonstrates high robustness against various attacks. Experimental results show structural similarity index metric values near unity, peak signal-to-noise ratios above 41 dB, and strong resilience to both singular and hybrid attacks, making it suitable for resource-constrained applications.