A High-Capacity Quantum Image Steganography Scheme Based on a Double-Layer Tortoise Shell Matrix

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This preprint studied a quantum color image steganography scheme designed to improve embedding capacity while maintaining imperceptibility and security. Using RGB-to-YCbCr conversion to separate luminance and chrominance per the human visual system, the authors embed secret data primarily into chrominance channels with a check-digit mechanism to reduce visual distortion, and use a double-layer “turtle shell” matrix so each coordinate can store more information. The scheme incorporates the Grover search algorithm to reduce the time complexity of searching embedding coordinates, and provides a quantum circuit diagram for embedding and extraction; it reports 5 bpp capacity with PSNR above 50 dB and improved payload versus existing methods, with the caveat that it is a preprint not yet peer reviewed. This paper does not explicitly discuss endometriosis or adenomyosis; it was included in the corpus via a keyword match in the upstream search index.

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Abstract

Abstract In recent years, quantum image steganography has attracted considerable attention; however, achieving high embedding capacity while preserving imperceptibility and security remains challenging. To address this issue, a quantum color image steganography scheme based on a double-layer turtle shell matrix is proposed.The scheme transforms RGB into the YCbCr color space to separate luminance and chrominance components according to the human visual system (HVS), and embeds secret information mainly into chrominance channels in combination with a check-digit mechanism to reduce visual distortion and enhance security. Meanwhile, the double-layer turtle shell matrix allows each coordinate to store more secret information. By jointly combining the YCbCr-based perceptual embedding strategy with the double-layer turtle shell matrix, the proposed scheme achieves 5 bpp embedding capacity while maintaining a PSNR above 50 dB.Moreover, the Grover search algorithm is incorporated to exploit quantum parallelism, significantly reducing the time complexity of searching embedding coordinates. A corresponding quantum circuit diagram is provided as a fundamental component for realizing the embedding and extraction processes. Experimental comparisons demonstrate that the proposed scheme outperforms existing methods in imperceptibility and embedding capacity, with a particularly notable improvement in payload.
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A High-Capacity Quantum Image Steganography Scheme Based on a Double-Layer Tortoise Shell Matrix | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article A High-Capacity Quantum Image Steganography Scheme Based on a Double-Layer Tortoise Shell Matrix Jia-Hao Huang, Hong-Mei Yang, Bin Yan, Dong-Huan Jiang, Hao-Ming Dang, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8787950/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract In recent years, quantum image steganography has attracted considerable attention; however, achieving high embedding capacity while preserving imperceptibility and security remains challenging. To address this issue, a quantum color image steganography scheme based on a double-layer turtle shell matrix is proposed.The scheme transforms RGB into the YCbCr color space to separate luminance and chrominance components according to the human visual system (HVS), and embeds secret information mainly into chrominance channels in combination with a check-digit mechanism to reduce visual distortion and enhance security. Meanwhile, the double-layer turtle shell matrix allows each coordinate to store more secret information. By jointly combining the YCbCr-based perceptual embedding strategy with the double-layer turtle shell matrix, the proposed scheme achieves 5 bpp embedding capacity while maintaining a PSNR above 50 dB.Moreover, the Grover search algorithm is incorporated to exploit quantum parallelism, significantly reducing the time complexity of searching embedding coordinates. A corresponding quantum circuit diagram is provided as a fundamental component for realizing the embedding and extraction processes. Experimental comparisons demonstrate that the proposed scheme outperforms existing methods in imperceptibility and embedding capacity, with a particularly notable improvement in payload. Quantum image steganography Double-layer turtle shell YCbCr color space Grover search algorithm Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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