研究目的
To propose an adaptive LSB quantum watermarking method using tri-way pixel value differencing for embedding watermarks in quantum images to protect copyright, aiming for high robustness, low distortion, and strong security.
研究成果
The proposed adaptive LSB quantum watermarking method effectively embeds watermarks with good visual quality, enhanced robustness, and improved security by leveraging tri-way pixel value differencing and adaptive embedding levels. It demonstrates feasibility through simulations and offers a novel approach in quantum image processing, with potential for future extensions to increase capacity and imperceptibility.
研究不足
The experiments are conducted on a classical computer due to the unavailability of a practical quantum computer, limiting real-world quantum system validation. The robustness analysis is focused on classical noise types, and the method may have constraints in handling other quantum-specific attacks or larger image sizes.
1：Experimental Design and Method Selection:
The method involves partitioning a quantum cover image into 2x2 blocks, calculating tri-way pixel value differences to classify blocks as smooth or edge areas, and embedding a scrambled and expanded watermark using adaptive k-bit LSB substitution based on block type. Quantum circuits for absolute value calculation and comparison are utilized.
2：Sample Selection and Data Sources:
Cover images (e.g., Lena, Peppers, Cameraman) of size 256x256 with 256 grayscales and a watermark image (Baboon) of size 128x128 with 256 grayscales are used in simulations.
3：List of Experimental Equipment and Materials:
A classical computer with Intel Core i5-7200U CPU, 2.70-GHz, 8.00-GB RAM, and MATLAB 2014b software for simulation.
4：70-GHz, 00-GB RAM, and MATLAB 2014b software for simulation.
Experimental Procedures and Operational Workflow:
4. Experimental Procedures and Operational Workflow: Steps include expanding and scrambling the watermark, transforming to quantum representation (NEQR), embedding using adaptive LSB substitution with parity bits, and extracting the watermark without the original cover image.
5：Data Analysis Methods:
Performance is evaluated using PSNR for visual quality and robustness under salt and pepper noise attacks, with comparisons to existing schemes.
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