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International Conference on Digital Society and Intelligent Systems (DSInS)

A Color Quantum Polar Coordinate Image Representation Model based on YCrCb Space

Dandan Ai, Zhanhong Wei, Jiahao Sun, Xiaolong Yang

Published Nov 7, 2025• 0 citations
Publisher

Abstract

To address the limitations of existing models that predominantly represent data in Cartesian coordinate systems and RGB color representations, this paper proposes YCrCbQPI (A Quantum Polar Coordinate Color Image Representation Model Based on YCrCb Color Space, YCrCb-QPI). This model integrates luminance and chrominance separation properties of YCrCb with the geometric invariance of logarithmic polar coordinates. Through a differentiated quantum encoding strategy, more qubits are allocated to critical luminance information while less sensitive chrominance information is assigned simplified encoding. Corresponding quantum state preparation circuits are also designed. Theoretical analysis indicates that compared to traditional RGB polar coordinate models, this model achieves significant savings in color information encoding resources while maintaining comparable visual fidelity. Furthermore, the model inherently possesses the rotation and scaling invariance of polar coordinates, establishing a robust foundation for developing efficient quantum image processing algorithms.

DOI
10.1109/dsins68311.2025.11329587

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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.