Spiking neural network based scrambled watermark hiding in low-frequency region of digital image

Malik, Sunesh; Kishore, R. Rama

doi:10.1080/02522667.2020.1723939

Cited by 5 publications

(1 citation statement)

References 33 publications

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“…From the illustrated results we can extrapolate that the proposed scheme is the most rapid, and basing in this fact, the proposed technique is appropriate to be used in real life. [21] 1.6766 0.0269 Ariatmanto et al [36] 0.2188 0.1250 Leung et al [37] 2.43 0.92 Mittal et al [38] 0.4071 0.2076 Su and Chen [39] 0.1948 5.8023 Malik and Rama Kishore et al [40] 1.26 3.38…”

Section: Operational Timementioning

confidence: 99%

Blind Digital Watermarking Framework Based on DTCWT and NSCT for Telemedicine Application

Nouioua¹,

Seddiki²,

Ghaz³

2020

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In this work, a blind watermarking framework for medical images based on Dual-Tree Complex Wavelet Transform (DTCWT) and Non-subsampled Contourlet Transform (NSCT) is proposed. The core idea of this technique is to embed the watermark in the appropriate NSCT sub-band obtained by decomposing the cover image low coefficients purchased from the DTCWT standing on a quantization embedding function, the extraction phase is done without the requirement of the original cover image, what makes it a fully blind process. As clarity and integrity of the retrieved watermark are mandatory, a series of tests were exerted to affirm the robustness of the proposed scheme. The effectiveness of the watermarking is validated by using the peak signal-to-noise ratio (PSNR) and the structural similarity index measure (SSIM) through experiments. Simulation results demonstrate the invisibility of the proposed method and its strong robustness against various attacks, including additive noise, image filtering, JPEG compression, amplitude scaling, rotation attack, and combinational attack. Furthermore, the method in hands outperformance within the quantitative comparisons with other techniques in the literature in terms of rapid execution time, and quality extraction of hidden information, and appropriateness to be integrated for secure exchange in the healthcare sector.

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