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A robust digital image watermarking technique in LWT-DCT domain using particle swarm optimization and statistical distortion correction

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Abstract

This paper introduces a robust digital image watermarking scheme operating in the LWT-DCT domain. To overcome the challenges associated with the conventional region or sub-band-specific embedding, the proposed scheme employs an adaptive region selection embedding algorithm. The selection of watermarking regions is based on visual and edge entropy characteristics, ensuring the preservation of visual imperceptibility in the watermarked image. Additionally, to eliminate the practices of using arbitrary gain factor while watermarking process, the proposed scheme utilizes the particle swarm optimization based algorithm for gain factor selection. This gain factor serves to (i) address the challenge of image-specific watermark selection and (ii) maintain tradeoff between conflicting parameters, namely robustness and imperceptibility. The method further introduces a statistical non-geometric distortion correction (N-GDC) algorithm to rectify the embedded image region affected by image processing attacks and to extract the watermark image. Through experimentation on an open-source image dataset, we achieve a PSNR of 48 dB for grayscale watermarked images subjected to various non-geometric attacks. The experimental results are also compared with state-of-the-art techniques to evaluate system resilience against different attacks. The obtained results indicate that the proposed scheme performs relatively better compared to state-of-the-art watermarking techniques.

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Data availability

The images used in this study are open-source and is publicly available at https://www.imageprocessingplace.com.

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Acknowledgements

The authors thank speech and image processing lab, Department of ECE, NIT Silchar for the computational facilities.

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Authors and Affiliations

  1. Department of Electronics and Communication Engineering, National Institute of Technology Silchar, Cachar, Assam, Pin - 788010, India

    Saharul Alom Barlaskar, Rabul Hussain Laskar & Taimoor Khan

  2. Department of Applied Mechanics and Biomedical Engineering, Indian Institute of Technology Madras, Madras, Tamil Nadu, Pin – 600036, India

    Anish Monsley Kirupakaran

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  1. Saharul Alom Barlaskar
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Correspondence to Saharul Alom Barlaskar.

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Barlaskar, S.A., Kirupakaran, A.M., Laskar, R.H. et al. A robust digital image watermarking technique in LWT-DCT domain using particle swarm optimization and statistical distortion correction. Multimed Tools Appl (2024). https://doi.org/10.1007/s11042-024-18982-7

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