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Hybrid Steerable Pyramid with DWT for Multiple Medical Image Watermarking and Extraction Using ICA

In: New Trends in Computational Vision and Bio-inspired Computing

Author

Listed:
  • R. Nanmaran

    (Annamalai University, Department of Electronics and Instrumentation Engineering)

  • G. Thirugnanam

    (Annamalai University, Department of Electronics and Instrumentation Engineering)

Abstract

The simplicity of digital media alteration and diffusion necessitates satisfied shield ahead of encryption. In decrypted form information’s are hidden in the form of watermarks. By embedding owner’s information, their property is protected and copyright protection is strengthened. To improve robustness and security multiple image watermarking is applied for the copyright of owner’s. Several literatures were assured about Discrete Wavelet Transform (DWT) watermarking schemes for data protection. On the other hand, DWT based watermarking schemes are establish to be fewer robust beside image processing attacks and the shift variance of Wavelet Packet Transform causes erroneous extraction. The multiple images watermarking technique based on hybrid Steerable Pyramid with Discrete Wavelet Transform (SPDWT) is proposed and it is compared with Integer Wavelet Transform (IWT). In this work, Input image is transformed by steerable pyramid results in various sub-bands and DWT is applied to these sub-bands. For watermark extraction, Pearson Independent component Analysis (ICA) is applied as it attains the new trait is that it not entails the renovation procedure in watermark extraction. The robustness of the proposed scheme is validated by different attacks to be applied on watermarked image. The performance measures like PSNR and Normalized Correlation are calculated to check the imperceptibility and robustness over integer wavelet transform.

Suggested Citation

  • R. Nanmaran & G. Thirugnanam, 2020. "Hybrid Steerable Pyramid with DWT for Multiple Medical Image Watermarking and Extraction Using ICA," Springer Books, in: S. Smys & Abdullah M. Iliyasu & Robert Bestak & Fuqian Shi (ed.), New Trends in Computational Vision and Bio-inspired Computing, pages 753-762, Springer.
  • Handle: RePEc:spr:sprchp:978-3-030-41862-5_75
    DOI: 10.1007/978-3-030-41862-5_75
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