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基于BEMD与DCT的彩色图像多重水印鲁棒算法

胡坤 李聪 胡建平 王小超 杜玲 王红飞

胡坤,李聪,胡建平,等. 基于BEMD与DCT的彩色图像多重水印鲁棒算法[J]. 北京航空航天大学学报,2023,49(1):165-176 doi: 10.13700/j.bh.1001-5965.2021.0214
引用本文: 胡坤,李聪,胡建平,等. 基于BEMD与DCT的彩色图像多重水印鲁棒算法[J]. 北京航空航天大学学报,2023,49(1):165-176 doi: 10.13700/j.bh.1001-5965.2021.0214
HU K,LI C,HU J P,et al. Robust multiple watermarking algorithm for color image via BEMD and DCT[J]. Journal of Beijing University of Aeronautics and Astronautics,2023,49(1):165-176 (in Chinese) doi: 10.13700/j.bh.1001-5965.2021.0214
Citation: HU K,LI C,HU J P,et al. Robust multiple watermarking algorithm for color image via BEMD and DCT[J]. Journal of Beijing University of Aeronautics and Astronautics,2023,49(1):165-176 (in Chinese) doi: 10.13700/j.bh.1001-5965.2021.0214

基于BEMD与DCT的彩色图像多重水印鲁棒算法

doi: 10.13700/j.bh.1001-5965.2021.0214
基金项目: 天津市高等学校基本科研业务费( 2018KJ222); 北京航空航天大学虚拟现实技术与系统国家重点实验室开放基金(BUAA-VR-16KF-23, BUAA-VR-17KF-04)
详细信息
    通讯作者:

    E-mail: wangxiaochao18@163.com

  • 中图分类号: TP391

Robust multiple watermarking algorithm for color image via BEMD and DCT

Funds: The Science & Technology Development Fund of Tianjin Education Commission for Higher Education (2018KJ222); The Open Funding Projection of State Key Laboratory of Virtual Reality Technology and Systems, Beihang University (BUAA-VR-16KF-23,BUAA-VR-17KF-04)
More Information
  • 摘要:

    为解决现有彩色图像水印算法容错性低及宿主图像与水印图像在嵌入时尺寸匹配问题,并提高算法抵御各种攻击的鲁棒性,提出一种基于二维经验模态分解(BEMD)和离散余弦变换(DCT)的彩色图像多重水印鲁棒算法。使用Arnold变换对3幅二值水印图像进行置乱,分别对彩色宿主图像的三通道进行BEMD,得到各通道的内蕴模态函数(IMF)和余量信息,选择各通道的第1个IMF(记作IMF1)作为水印嵌入层,对每个通道的IMF1分割成不重叠子块后进行DCT;再将置乱后的二值水印图像依次重复嵌入在各通道子块经过之字形(Zigzag)扫描后的中频系数中,使用逆Zigzag扫描和逆DCT得到各通道嵌入水印信息后的IMF1,并与每个通道其余的IMF及余量重建得到嵌入水印后的彩色图像。水印提取为嵌入过程的逆过程,算法可以实现彩色图像嵌入水印的盲提取。在水印提取过程中对重复嵌入提取到的水印图像使用投票策略,增强了算法的容错性。大量实验结果表明:嵌入水印后的图像峰值信噪比(PSNR)在34 dB以上,水印信息具有较高的不可见性;对嵌入多重水印后的宿主图像进行大尺寸剪切、椒盐噪声等攻击实验,提取到的水印图像与原始图像的归一化系数均在0.96以上,且可达到1,水印信息提取完整清晰可辨。与现有大量彩色图像水印算法相比,所提算法具有较强抵御各种攻击的能力,同时嵌入水印后图像具有较高的不可见性。

     

  • 图 1  彩色图像BEMD

    Figure 1.  Example of colored image BEMD

    图 2  Zigzag扫描

    Figure 2.  Curve of Zigzag scan

    图 3  本文算法流程

    Figure 3.  Framework of the proposed algorithm

    图 4  水印提取投票机制

    Figure 4.  Mechanism of watermark image extraction voting mechanism

    图 5  不可感知性实验结果

    Figure 5.  Experimental results of invisibility

    图 6  大比例剪切攻击实验结果

    Figure 6.  Experimental results of large scale cropping attack

    图 7  椒盐噪声攻击实验结果

    Figure 7.  Experimental results of salt and pepper noise attack

    图 8  高斯噪声攻击实验结果

    Figure 8.  Experimental results of Gaussian noise attack

    图 9  直方图均衡化攻击实验结果

    Figure 9.  Experimental results of histogram equalization attack

    图 10  滤波器攻击实验结果

    Figure 10.  Experimental results of filter attack

    图 11  图像锐化攻击实验结果

    Figure 11.  Experimental results of sharpening attack

    图 12  JPEG压缩攻击实验结果

    Figure 12.  Experimental results of JPEG compression attack

    图 13  散斑噪声攻击实验结果

    Figure 13.  Experimental results of speckle noise attack

    图 14  图像缩放攻击实验结果

    Figure 14.  Experimental results of image scaling attack

    图 15  Aerials数据库中遥感图像攻击实验结果

    Figure 15.  Experimental results of remote sensing image attack in aerials database

    图 16  左上角25%剪切攻击实验结果

    Figure 16.  Experimental results of 25% shear attack in the upper left corner

    图 17  高斯噪声攻击实验结果

    Figure 17.  Experimental results of Gaussian noise attack

    图 18  3%的椒盐噪声攻击实验结果

    Figure 18.  Results of 3% salt and pepper noise attack

    表  1  本文算法与彩色图像水印算法[6 , 28]在不同攻击下的NC值对比

    Table  1.   Comparison with color image watermarking algorithm[6 , 28] under different attacks NC values

    攻击类型攻击强度Lena图像NC值
    (文献[6])
    Lena图像NC值
    (文献[28])
    Lena图像NC值
    (所提算法)
    Baboon图像NC值
    (所提算法)
    Airplane图像NC值
    (所提算法)
    水印1水印2水印1水印1水印2水印3水印1水印2水印3水印1水印2水印3
    剪切攻击25%0.9921.0000.8731.0001.0001.0001.0001.0001.0001.0001.0001.000
    高斯低通滤波[2,2]0.9380.9720.8551.0001.0000.9990.9830.9800.9711.0001.0001.000
    中值滤波[3,3]0.9950.9970.4100.9480.9620.9070.8600.9070.8560.9360.9560.921
    图像锐化R=20.9981.0000.9901.0001.0001.0001.0001.0001.0001.0001.0001.000
    椒盐噪声3%0.8970.9510.9841.0001.0001.0001.0000.9980.9991.0001.0001.000
    高斯噪声0.0050.9120.9260.7651.0001.0001.0000.9960.9980.9950.9981.0001.000
    JPEG压缩Q=601.0001.0000.9061.0001.0001.0001.0000.9991.0001.0001.0001.000
    图像缩放0.25~40.9900.9950.9381.0001.0001.0001.0000.9991.0001.0001.0001.000
    下载: 导出CSV

    表  2  本文算法与彩色图像水印算法[7-10]在不同宿主图像下进行不同攻击的NC值对比

    Table  2.   Comparison with color image watermarking algorithms[7-10] for different attacks NC values under different host images

    攻击类型攻击强度Lena图像NC值
    文献[7]文献[8]文献[9]文献[10]本文所提算法
    水印1水印2水印3
    JPEG压缩300.758 30.93~0.940.91~0.920.905 10.847 10.939 60.875 9
    JPEG压缩900.958 61.000 01.000 00.995 91.000 01.000 01.000 0
    椒盐噪声0.020.9980.96~0.970.99~10.991 11.000 01.000 01.000 0
    椒盐噪声0.10.991 70.94~0.950.97~0.980.960 70.993 80.998 10.997 6
    高斯噪声0.10.874 31.000 00.73~0.750.940 61.000 01.000 01.000 0
    高斯噪声0.60.790 50.95~0.960.55~0.560.828 31.000 01.000 01.000 0
    缩放4~0.250.999 80.79~0.800.67~0.680.870 21.000 01.000 01.000 0
    剪切25%0.889 50.73~0.750.8~0.810.772 51.000 01.000 01.000 0
    剪切50%0.833 50.600 00.52~0.530.514 11.000 01.000 01.000 0
    攻击类型攻击强度Airplane图像NC值
    文献[7]文献[8]文献[9]文献[10]本文所提算法
    水印1水印2水印3
    JPEG压缩300.778 80.94~0.950.90~0.910.920 40.853 40.931 40.842 8
    JPEG压缩900.967 51.0001.0000.998 61.000 01.000 01.000 0
    椒盐噪声0.020.9990.94~0.950.99~10.995 81.000 01.000 01.000 0
    椒盐噪声0.10.987 50.92~0.930.98~0.990.978 70.997 60.998 10.995 3
    高斯噪声0.10.888 21.000 00.78~0.790.957 71.000 01.000 01.000 0
    高斯噪声0.60.592 80.92~0.930.57~0.580.855 01.000 01.000 01.000 0
    缩放4~0.250.926 50.78~0.790.69~0.700.877 31.000 01.000 01.000 0
    剪切25%0.889 50.74~0.760.8~0.810.772 51.000 01.000 01.000 0
    剪切50%0.833 50.600 00.52~0.530.514 11.000 01.000 01.000 0
    下载: 导出CSV
  • [1] ATTAULLAH, SHAH T, JAMAL S S. An improved chaotic cryptosystem for image encryption and digital watermarking[J]. Wireless Personal Communications, 2020, 110(3): 1429-1442. doi: 10.1007/s11277-019-06793-1
    [2] THANKI R, DWIVEDI V, BORISAGAR K. A hybrid watermarking scheme with CS theory for security of multimedia data[J]. Journal of King Saud University-Computer and Information Sciences, 2019, 31(4): 436-451. doi: 10.1016/j.jksuci.2017.05.005
    [3] KARAJEH H, KHATIB T, RAJAB L, et al. A robust digital audio watermarking scheme based on DWT and Schur decomposition[J]. Multimedia Tools and Applications, 2019, 78(13): 18395-18418. doi: 10.1007/s11042-019-7214-3
    [4] LAKRISSI Y, SAAIDI A, ESSAHLAOUI A. Novel dynamic color image watermarking based on DWT-SVD and the human visual system[J]. Multimedia Tools and Applications, 2018, 77(11): 13531-13555. doi: 10.1007/s11042-017-4974-5
    [5] ABDULRAHMAN A K, OZTURK S. A novel hybrid DCT and DWT based robust watermarking algorithm for color images[J]. Multimedia Tools and Applications, 2019, 78(12): 17027-17049. doi: 10.1007/s11042-018-7085-z
    [6] ROY S, PAL A K. A blind DCT based color watermarking algorithm for embedding multiple watermarks[J]. AEU-International Journal of Electronics and Communications, 2017, 72: 149-161.
    [7] SU Q T, LIU Y H, LIU D C, et al. A new watermarking scheme for colour image using QR decomposition and ternary coding[J]. Multimedia Tools and Applications, 2019, 78(7): 8113-8132. doi: 10.1007/s11042-018-6632-y
    [8] SU Q T, YUAN Z H, LIU D C. An approximate schur decomposition-based spatial domain color image watermarking method[J]. IEEE Access, 2019, 7: 4358-4370. doi: 10.1109/ACCESS.2018.2888857
    [9] LIU D C, YUAN Z H, SU Q T. A blind color image watermarking scheme with variable steps based on Schur decomposition[J]. Multimedia Tools and Applications, 2020, 79(11-12): 7491-7513. doi: 10.1007/s11042-019-08423-1
    [10] SU Q T, ZHANG X F, WANG G. An improved watermarking algorithm for color image using Schur decomposition[J]. Soft Computing, 2020, 24(1): 445-460. doi: 10.1007/s00500-019-03924-5
    [11] HUANG N E, SHEN Z, LONG S R, et al. The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis[J]. Proceedings of the Royal Society of London Series A:Mathematical, Physical and Engineering Sciences, 1998, 454(1971): 903-995. doi: 10.1098/rspa.1998.0193
    [12] 李翠芸, 曹潇男, 姬红兵, 等. 基于偏微分方程的快速二维经验模态分解方法及其应用[J]. 计算机辅助设计与图形学学报, 2014, 26(7): 1143-1150.

    LI C Y, CAO X N, JI H B, et al. A fast bidimensional empirical mode decomposition based on partial differential equation and its application on image processing[J]. Journal of Computer-Aided Design & Computer Graphics, 2014, 26(7): 1143-1150(in Chinese).
    [13] DING S F, DU P, ZHAO X Y, et al. BEMD image fusion based on PCNN and compressed sensing[J]. Soft Computing, 2019, 23(20): 10045-10054. doi: 10.1007/s00500-018-3560-8
    [14] CHEN Y Q, ZHANG L N, ZHAO B B. Identification of the anomaly component using BEMD combined with PCA from element concentrations in the Tengchong tin belt, SW China[J]. Geoscience Frontiers, 2019, 10(4): 1561-1576. doi: 10.1016/j.gsf.2018.09.015
    [15] AN F P, LIU Z W. Bi-dimensional empirical mode decomposition (BEMD) algorithm based on particle swarm optimization-fractal interpolation[J]. Multimedia Tools and Applications, 2019, 78(12): 17239-17264. doi: 10.1007/s11042-018-7097-8
    [16] MA X M, ZHOU X W, AN F P. Bi-dimensional empirical mode decomposition (BEMD) and the stopping criterion based on the number and change of extreme points[J]. Journal of Ambient Intelligence and Humanized Computing, 2020, 11(2): 623-633. doi: 10.1007/s12652-018-0955-4
    [17] NUNES J C, BOUAOUNE Y, DELECHELLE E, et al. Image analysis by bidimensional empirical mode decomposition[J]. Image and Vision Computing, 2003, 21(12): 1019-1026. doi: 10.1016/S0262-8856(03)00094-5
    [18] REN G H, HAN J N, FU J H, et al. Asymmetric multiple-image interference cryptosystem using discrete cosine transform and conditional decomposition[J]. Optical Review, 2020, 27(1): 1-8. doi: 10.1007/s10043-019-00552-0
    [19] MOGHADDASI Z, JALAB H A, NOOR R M. Image splicing forgery detection based on low-dimensional singular value decomposition of discrete cosine transform coefficients[J]. Neural Computing and Applications, 2019, 31(11): 7867-7877. doi: 10.1007/s00521-018-3586-y
    [20] ZHANG L N, WEI D Y. Dual DCT-DWT-SVD digital watermarking algorithm based on particle swarm optimization[J]. Multimedia Tools and Applications, 2019, 78(19): 28003-28023. doi: 10.1007/s11042-019-07902-9
    [21] ABBAS N A. Image encryption based on independent component analysis and arnold’s cat map[J]. Egyptian Informatics Journal, 2016, 17(1): 139-146. doi: 10.1016/j.eij.2015.10.001
    [22] LI X S, LI T Y, WU J, et al. Joint image compression and encryption based on sparse Bayesian learning and bit-level 3D Arnold cat maps[J]. PLoS One, 2019, 14(11): 0224382. doi: 10.1371/journal.pone.0224382
    [23] XIE J H, WU D L, WANG J, et al. The analysis of additive noise of thermal test low-frequency cable fault detection based on M sequence correlation algorithm[J]. Cluster Computing, 2019, 22(4): 9303-9312.
    [24] 王小超, 胡坤, 胡建平. 结合BEMD与Hilbert曲线的重复嵌入图像水印算法[J]. 计算机辅助设计与图形学学报, 2020, 32(2): 287-296.

    WANG X C, HU K, HU J P. Repeated embedding algorithm for image watermarking based on BEMD and Hilbert curve[J]. Journal of Computer-Aided Design & Computer Graphics, 2020, 32(2): 287-296(in Chinese).
    [25] WANG X C, HU K, HU J P, et al. Robust and blind image watermarking via circular embeddingand bidimensional empirical mode decomposition[J]. The Visual Computer, 2020, 36(10-12): 2201-2214. doi: 10.1007/s00371-020-01909-2
    [26] HONG D, CHO H, LEE S, et al. Volumetric image reconstruction in a dental panoramic imaging system with a limited-angle zigzag scan geometry[J]. Journal of the Korean Physical Society, 2013, 62(2): 333-338. doi: 10.3938/jkps.62.333
    [27] HUYNH-THU Q, GHANBARI M. Scope of validity of PSNR in image/video quality assessment[J]. Electronics Letters, 2008, 44(13): 800. doi: 10.1049/el:20080522
    [28] SU Q T, WANG G, JIA S L, et al. Embedding color image watermark in color image based on two-level DCT[J]. Signal, Image and Video Processing, 2015, 9(5): 991-1007. doi: 10.1007/s11760-013-0534-2
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出版历程
  • 收稿日期:  2021-04-22
  • 录用日期:  2021-06-06
  • 网络出版日期:  2023-01-16
  • 刊出日期:  2021-06-15

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