量子图像水印技术在电力大数据中的应用
|
摘要
为保证电力大数据的安全和处理效果,本文提出一种基于量子图像水印技术的嵌入及提取方法。该方法首先将原载体灰色图像用量子表示,并利用量子小波变换四次分解原载体图像得到子图,再通过量子离散余弦变换对子图进行系数转换。通过对系数矩阵进行奇异值分解得到对角矩阵,再利用量子广义Arnold变换和Logistic映射对水印进行置乱,并进行奇异值分解,从而实现量子水印的嵌入。嵌入的水印图像被分解后,每个像素的灰度信息为一个均衡的量子叠加态,测量后整幅图像为一个均匀的白噪声。水印图像的提取过程为嵌入的逆过程。仿真结果表明,相对经典图像水印,量子图像水印技术计算复杂度更低,计算速度更快,嵌入的水印图像具有很好的安全性,并且不影响载体图像的视觉效果。
In order to ensure the security and processing effect of power big data,this paper presents an embedding and extracting method based on quantum image watermarking technology. In this method,the gray image of the original carrier is first represented by quantum,and the sub-graph is obtained by decomposing the image of the original carrier four times with the quantum wavelet transform. And the coefficients of the sub-graph are transformed by quantum discrete cosine transform. The diagonal matrix is obtained by singular value decomposition of coefficient matrix,then the watermark is scrambled by quantum generalized Arnold transform and Logistic map,and singular value decomposition is carried out to realize the embedding of quantum watermark. After the embedded watermark image is decomposed,the gray level information of each pixel is an equalized quantum superposition state,and the whole image is measured as a uniform white noise. The extraction process of watermark image is an inverse process of embedding. Simulation results show that compared with classical image watermarking,quantum image watermarking has lower computational complexity,faster computation speed,better security of embedded watermark image,and does not affect the visual effect of carrier image.
In order to ensure the security and processing effect of power big data,this paper presents an embedding and extracting method based on quantum image watermarking technology. In this method,the gray image of the original carrier is first represented by quantum,and the sub-graph is obtained by decomposing the image of the original carrier four times with the quantum wavelet transform. And the coefficients of the sub-graph are transformed by quantum discrete cosine transform. The diagonal matrix is obtained by singular value decomposition of coefficient matrix,then the watermark is scrambled by quantum generalized Arnold transform and Logistic map,and singular value decomposition is carried out to realize the embedding of quantum watermark. After the embedded watermark image is decomposed,the gray level information of each pixel is an equalized quantum superposition state,and the whole image is measured as a uniform white noise. The extraction process of watermark image is an inverse process of embedding. Simulation results show that compared with classical image watermarking,quantum image watermarking has lower computational complexity,faster computation speed,better security of embedded watermark image,and does not affect the visual effect of carrier image.
引文
[1]陈兴蜀,杨露,罗永刚.大数据安全保护技术[J].工程科学与技术,2017,49(05):1-12.CHEN Xingshu,YANG Lu,LUO Yonggang. Big data securitytechnology[J]. Advanced Engineering Sciences,2017,49(05):1-12.
[2]张东霞,苗新,刘丽平,等.智能电网大数据技术发展研究[J].中国电机工程学报,2015,35(01):2-12.ZHANG Dongxia,MIAO Xing,LIU Liping,et al. Research on thestrategy of smart grid big data[J]. Proceedings of the CSEE,2015,35(01):2-12.
[3]曾四鸣.大数据挖掘技术在电力行业中的应用[J].电力大数据,2017,20(09):81-84.ZENG Siming,The application of big data mining(DM)technologyin power system[J]. Power Systems and Big Data,2017,20(09):81-84.
[4]何湘宁,石巍,李武华,等.基于大数据的大容量电力电子系统可靠性研究[J].中国电机工程学报,2017,37(01):209-221.HE Xiangning,SHI Wei,LI Wuhua,et al. Reliability enhancementof power electronic system by big data science[J]. Proceedings ofthe CSEE,2017,37(01):209-221.
[5] ERIC C. ROWELL,ZHENGHAN WANG. Mathematics of topologicalquantum computing[J]. Bulletin of the American MathematicalSociety,2018,55(02):183-238.
[6] YAN F,ILIYASU A M,VENEGAS-ANDRACA S E. A survey ofquantum image representations[J]. Quantum InformationProcessing,2016,15(1):1-35.
[7] RIGUI Zhou,CANYUN TAN,HOU Ian. Global and local translationdesigns of quantum image based on FRQI[J]. International Journal ofTheoretical Physics,2017,56(04):1382-1398.
[8]李涛,何煌兴,瞿治国.一种基于含水印量子图像的自适应量子隐写算法[J].计算机应用研究,2018,35(2):503-506.LI Tao,HE Huangxing,ZHAI Zhiguo. Novel self-adaptive quantumsteganography algorithm based on quantum image withwatermarking[J]. Application Research of Computers,2018,35(02):503-506.
[9]吴佳楠,王世刚,张迪.融合量子密钥真随机性的二值图像水印[J].光学精密工程,2017,25(11):2968-2974.WU Jianan,WANG Shigang,ZHANG Di. Binary image watermarkfusion based on quantum key true randomness[J]. Optics andPrecision Engineering,2017,25(11):2968-2974.
[10] MA Q,ZHANG J,SUN C,et al. Drought characteristics and predictionduring pasture growing season in Xilingol grassland,northern China[J]. Theoretical and Applied Climatology,2018,133(01-02):165-178.
[11] YAN F,ILIYASU A M,SUN B,et al. A duple watermarking strategyfor multi-channel quantum images[J]. Quantum InformationProcessing,2015,14(05):1675-1692.
[12] JIANG N,ZHAO N,WANG L. LSB based quantum image steganographyalgorithm[J]. International Journal of Theoretical Physics,2016,55(01):107-123.
[13] El-Latif A A A,Abd-El-Atty B,Hossain M S,et al. Efficientquantum information hiding for remote medical image sharing[J]. IEEE Access,2018,6:21075-21083.
[14] HEIDARI S,NASERI M. A novel LSB based quantum watermarking[J]. International Journal of Theoretical Physics,2016,55(10):4205-4218.
[15] CARAIMAN S,MANTA V I. Image segmentation on a quantumcomputer[J]. Quantum Information Processing,2015,14(05):1693-1715.
[16]佟德宇,任娜,朱长青.基于压缩感知的图像水印信息生成算法[J].华中科技大学学报(自然科学版),2017,45(08):38-41.TONG Deyu,REN Na,ZHU Changqing. Image watermarkinginformation generation and reconstruction algorithm based oncompressive sensing[J]. Journal of Huazhong University ofScience and Technology(Natural Science Edition),2017,45(08):38-41.
[17] ZHOU N R,HUA T X,GONG L H,et al. Quantum image encryptionbased on generalized Arnold transform and double random-phaseencoding[J]. Quantum Information Processing,2015,14(04):1193-1213.
[18] KAJO I,KAMEL N,RUICHEK Y,et al. SVD-based tensor-completiontechnique for background initialization[J]. IEEE Transactions on ImageProcessing,2018,27(06):3114-3126.
[19]赵永良,章剑光,张永建.基于图像技术的电网运行态势分析及其应用[J]浙江电力. 2017,36(12):81-85.ZHAO Yongliang,ZHANG Jianguang,ZHANG Yongjian. Powergrid operation situation analysis based on image technology and itsapplication[J]. Zhejiang Electric Power,2017,36(12):81-85.
[2]张东霞,苗新,刘丽平,等.智能电网大数据技术发展研究[J].中国电机工程学报,2015,35(01):2-12.ZHANG Dongxia,MIAO Xing,LIU Liping,et al. Research on thestrategy of smart grid big data[J]. Proceedings of the CSEE,2015,35(01):2-12.
[3]曾四鸣.大数据挖掘技术在电力行业中的应用[J].电力大数据,2017,20(09):81-84.ZENG Siming,The application of big data mining(DM)technologyin power system[J]. Power Systems and Big Data,2017,20(09):81-84.
[4]何湘宁,石巍,李武华,等.基于大数据的大容量电力电子系统可靠性研究[J].中国电机工程学报,2017,37(01):209-221.HE Xiangning,SHI Wei,LI Wuhua,et al. Reliability enhancementof power electronic system by big data science[J]. Proceedings ofthe CSEE,2017,37(01):209-221.
[5] ERIC C. ROWELL,ZHENGHAN WANG. Mathematics of topologicalquantum computing[J]. Bulletin of the American MathematicalSociety,2018,55(02):183-238.
[6] YAN F,ILIYASU A M,VENEGAS-ANDRACA S E. A survey ofquantum image representations[J]. Quantum InformationProcessing,2016,15(1):1-35.
[7] RIGUI Zhou,CANYUN TAN,HOU Ian. Global and local translationdesigns of quantum image based on FRQI[J]. International Journal ofTheoretical Physics,2017,56(04):1382-1398.
[8]李涛,何煌兴,瞿治国.一种基于含水印量子图像的自适应量子隐写算法[J].计算机应用研究,2018,35(2):503-506.LI Tao,HE Huangxing,ZHAI Zhiguo. Novel self-adaptive quantumsteganography algorithm based on quantum image withwatermarking[J]. Application Research of Computers,2018,35(02):503-506.
[9]吴佳楠,王世刚,张迪.融合量子密钥真随机性的二值图像水印[J].光学精密工程,2017,25(11):2968-2974.WU Jianan,WANG Shigang,ZHANG Di. Binary image watermarkfusion based on quantum key true randomness[J]. Optics andPrecision Engineering,2017,25(11):2968-2974.
[10] MA Q,ZHANG J,SUN C,et al. Drought characteristics and predictionduring pasture growing season in Xilingol grassland,northern China[J]. Theoretical and Applied Climatology,2018,133(01-02):165-178.
[11] YAN F,ILIYASU A M,SUN B,et al. A duple watermarking strategyfor multi-channel quantum images[J]. Quantum InformationProcessing,2015,14(05):1675-1692.
[12] JIANG N,ZHAO N,WANG L. LSB based quantum image steganographyalgorithm[J]. International Journal of Theoretical Physics,2016,55(01):107-123.
[13] El-Latif A A A,Abd-El-Atty B,Hossain M S,et al. Efficientquantum information hiding for remote medical image sharing[J]. IEEE Access,2018,6:21075-21083.
[14] HEIDARI S,NASERI M. A novel LSB based quantum watermarking[J]. International Journal of Theoretical Physics,2016,55(10):4205-4218.
[15] CARAIMAN S,MANTA V I. Image segmentation on a quantumcomputer[J]. Quantum Information Processing,2015,14(05):1693-1715.
[16]佟德宇,任娜,朱长青.基于压缩感知的图像水印信息生成算法[J].华中科技大学学报(自然科学版),2017,45(08):38-41.TONG Deyu,REN Na,ZHU Changqing. Image watermarkinginformation generation and reconstruction algorithm based oncompressive sensing[J]. Journal of Huazhong University ofScience and Technology(Natural Science Edition),2017,45(08):38-41.
[17] ZHOU N R,HUA T X,GONG L H,et al. Quantum image encryptionbased on generalized Arnold transform and double random-phaseencoding[J]. Quantum Information Processing,2015,14(04):1193-1213.
[18] KAJO I,KAMEL N,RUICHEK Y,et al. SVD-based tensor-completiontechnique for background initialization[J]. IEEE Transactions on ImageProcessing,2018,27(06):3114-3126.
[19]赵永良,章剑光,张永建.基于图像技术的电网运行态势分析及其应用[J]浙江电力. 2017,36(12):81-85.ZHAO Yongliang,ZHANG Jianguang,ZHANG Yongjian. Powergrid operation situation analysis based on image technology and itsapplication[J]. Zhejiang Electric Power,2017,36(12):81-85.