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This work provides a novel method of watermarking digital images by integrating Discrete Wavelet Transform (DWT) along with singular value decomposition (SVD) utilizing a differential embedding technique to incorporate the singular values associated with the watermark within the LH sub-band of the host image. In the extraction phase, the singular values of the watermark are generated by subtracting their singular values from two sub-bands where the watermark has been embedded. They are LH and HL sub-bands. With average PSNR, RMSE, and SSIM values of 49.4818, 0.8024, and 0.9982, respectively, and a high data payload, the experimental findings indicate that the proposed approach successfully meets the need for imperceptibility. Moreover, it offers outstanding resilience against various geometrical and image processing assaults, such as gamma correction, blurring, scaling, rotation, Gaussian, and salt & pepper noise.

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Image Watermarking Based on DWT-SVD Using Differential Embedding

  • 会议论文

  • 发表日期：

    2025年

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  • Bhupendra Singh,
  • Bharathi Chidirala,
  • Bijayananda Patnaik,
  • Bibhudendra Acharya

摘要

This work provides a novel method of watermarking digital images by integrating Discrete Wavelet Transform (DWT) along with singular value decomposition (SVD) utilizing a differential embedding technique to incorporate the singular values associated with the watermark within the LH sub-band of the host image. In the extraction phase, the singular values of the watermark are generated by subtracting their singular values from two sub-bands where the watermark has been embedded. They are LH and HL sub-bands. With average PSNR, RMSE, and SSIM values of 49.4818, 0.8024, and 0.9982, respectively, and a high data payload, the experimental findings indicate that the proposed approach successfully meets the need for imperceptibility. Moreover, it offers outstanding resilience against various geometrical and image processing assaults, such as gamma correction, blurring, scaling, rotation, Gaussian, and salt & pepper noise.