| 摘要: |
| 目的 为提高印刷量子点图像的鲁棒性、识读速度和信息隐藏容量，提出一种可靠性复合光谱印刷量子点图像编解码算法。方法 首先结合ChaCha20加密算法、SHA-256哈希算法、(331, 225, 367)卷积码和交织编码，将明文信息编码成具有安全验证和纠错能力的二进制秘密信息，再插入伪随机同步信息，并进行掩膜矩阵置乱，映射成可通过相邻数据联合解算的印刷量子点图像，最后利用2组印刷量子点图像对载体图像进行信息调制，实现复合光谱大容量信息隐藏。结果 实验结果显示，生成的复合光谱印刷量子点图像可抵抗20%以内的噪声攻击，识读时间在0.1 s左右，嵌入率为2 bpp，与原始载体图像的峰值信噪比(Peak Signal-to-Noise Ratio，PSNR)约为40 dB，结构相似性(Structural Similarity，SSIM)约为0.97。结论 本算法与其他算法相比，在高嵌入率下具有更高的鲁棒性和更好的不可见性，识读速度更快。 |
| 关键词: 印刷量子点图像 复合光谱 卷积码 信息隐藏 |
| DOI：10.19554/j.cnki.1001-3563.2025.07.021 |
| 分类号: |
| 基金项目:国家自然科学基金面上项目(61972042);北京市基金-市教委联合项目(KZ202010015023);北京印刷学院科研平台建设项目(KYCPT202509);北京印刷学院信息与通信工程一级学科博士点培育项目(21090525004) |
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| Encoding and Decoding Algorithms for Image Information of Composite Spectrum Based on Printed Quantum Dots ZHAO Wenkang, CAO Peng |
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ZHAO Wenkang, CAO Peng
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(Beijing Key Laboratory of Signal and Information Processing for High-end Printing Equipment, Beijing Institute of Graphic Communication, Beijing 102600, China)
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| Abstract: |
| In order to improve the robustness, reading speed and information hiding capacity of printed quantum dot images, the work aims to propose a reliable encoding and decoding algorithm for composite spectral printed quantum dot image. Firstly, ChaCha20 encryption algorithm, SHA-256 hash algorithm, (331, 225, 367) convolutional code and interlacing coding were combined to encode the plaintext information into binary secret information with security verification and error correction capabilities, and then pseudo random synchronization information was inserted, and mask matrix scrambling was carried out, which was mapped into a printed quantum dot image that could be solved jointly by adjacent data. Finally, two sets of printed quantum dot images were used to modulate the carrier image to realize the large-capacity information hiding of composite spectrum. The experimental results showed that the generated composite spectral printed quantum dot image could resist the noise attack within 20%, the reading time was about 0.1 s, the embedding rate was 2 bpp, and the Peak Signal-to-Noise Ratio (PSNR) value was about 40 dB compared with the original carrier image and the structural similarity (SSIM) value was about 0.97. Compared with other algorithms, this algorithm has higher robustness, better invisibility and faster reading speed under high embedding rate. |
| Key words: printed quantum dot image composite spectrum convolutional coding information hiding |
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