基于特征点的遥感影像地图版权保护方法的研究
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摘要
随着互联网技术的飞速发展,数字地图产品的存储与应用越来越广泛。遥感影像地图作为一种新兴的数字地图产品广泛的应用在军事测绘和地理信息导航领域。但是,如何在应用中保护遥感影像地图产品的版权成为一大研究热点。面对这样的问题,人们提出数字水印技术用于产品的版权保护。数字水印技术通过将水印信息按照特定的形式加载到需要保护的数字产品中以此达到版权保护的目的。同时遥感影像地图数字水印算法还存在以下几个问题：水印嵌入位置难以确定,过去的方法多是在空域或是频域选择若干位置,直接进行水印的嵌入,这些方法仅能够在某几种特殊攻击的情况下具有良好的效果,通用性较差；水印扰动方法效果不佳,水印扰动方法的好坏直接影响到对原始地图数据的修改量的多少；水印算法的设计没有结合遥感影像地图自身的特点,多数水印算法仅是从影像地图中的图像数据角度考虑水印的嵌入。
针对以上问题本文提出了一种结合遥感影像地图自身特点的,用于遥感影像地图版权保护的盲水印算法。该算法利用Harris特征点的稳定性和小波的多级特性,对各级小波的低频系数分别进行Harris特征点提取,对获取的特征点采用量纲同一结合动态聚类分析方法获取特征代表点,这种特征点提取方法具有更高的可重定位性,能够增强算法的鲁棒性；然后以特征代表点位置为参考,将置乱的二值图像信息以提出的扰动方法嵌入到小波系数中,该扰动嵌入方法能够在最大程度上保证水印的不可见性的同时提高水印的抗攻击性。该算法在提取阶段结合遥感影像地图属性数据的不易变性,将属性数据中的地理坐标数据作为密钥,采用基于密钥的水印提取策略和直接逆反嵌入过程的提取策略获取水印数据,选择其中最优的作为水印提取结果。该提取方法既提高了水印算法的效率又保障了水印提取的完整性。
通过实验表明,遥感影像地图在根据本文提出的算法嵌入水印后具有良好的不可感知性,而且该方法对于几何攻击、滤波攻击、噪声攻击、JPEG压缩攻击等攻击方法都表现出良好的鲁棒性。
With the rapid development of the network technology, digital map products for the storage and application are even more extensive. As a new digital map product, remote sensing image map is widely used in the field of military mapping and geographic information navigation. How to protect copyright of remote sensing image map products has become a major research focus. Faced with this problem, people have proposed digital watermarking technology to protect the copyright of the products. Digital watermark technology loads the watermark such as text, binary image or a sequence of the number into the digital products by a particular way in order to protect the copyright. There are several problems in the remote sensing image map's watermarking algorithms:It is difficult to determine the location for embedding watermark, past approaches choose some positions in the pixels or the frequency domain of the map to embed the watermark directly. These approaches could have good effects in a few special cases of attacks, but are not versatile; The perturbation method of watermark doesn't have good performance. The perturbation method has a direct impact on the amount of the change in remote sensing image map's data; The characteristic of the remote sensing image map is not considered in the watermarking algorithms. Most watermarking algorithms are just designed using the data of the image.
To solve the above problems, combined with the remote sensing image map's characteristics, this dissertation presents a blind watermarking algorithm for copyright protection. The algorithm uses the stability of harris feature points and the characteristics of the wavelet multi-level to get the feature points on the field at all level of low frequency wavelet coefficient. The feature points are unified in the same dimension and classified into several clusters to get the representative points. Then a representative point of the cluster is selected to locate the reference point. The representative points got by this method are more relocatable. And this method enhances the robustness of the algorithm. At last the scrambled binary image information is embedded into the wavelet coefficient by the proposed perturbation method. The proposed perturbation method ensures the invisibility in maximum extent also improves the resistance to attacks. The invariance of the attribute data is considered in the extraction process. The proposed algorithm uses two methods to get the watermark. First method uses the geographical coordinates of the attribute data as a secret key to get watermark. While another way gets the watermark uses the embedding method as a reference. The proposed extraction method not only ensures the efficiency of the algorithm but also protects the integrity of the extracted watermark.
The experimental results show that the proposed algorithm has good performance of the invisibility and is effective against the geometric attack, filtering attack, noise attack, jpeg compression attack.
针对以上问题本文提出了一种结合遥感影像地图自身特点的,用于遥感影像地图版权保护的盲水印算法。该算法利用Harris特征点的稳定性和小波的多级特性,对各级小波的低频系数分别进行Harris特征点提取,对获取的特征点采用量纲同一结合动态聚类分析方法获取特征代表点,这种特征点提取方法具有更高的可重定位性,能够增强算法的鲁棒性；然后以特征代表点位置为参考,将置乱的二值图像信息以提出的扰动方法嵌入到小波系数中,该扰动嵌入方法能够在最大程度上保证水印的不可见性的同时提高水印的抗攻击性。该算法在提取阶段结合遥感影像地图属性数据的不易变性,将属性数据中的地理坐标数据作为密钥,采用基于密钥的水印提取策略和直接逆反嵌入过程的提取策略获取水印数据,选择其中最优的作为水印提取结果。该提取方法既提高了水印算法的效率又保障了水印提取的完整性。
通过实验表明,遥感影像地图在根据本文提出的算法嵌入水印后具有良好的不可感知性,而且该方法对于几何攻击、滤波攻击、噪声攻击、JPEG压缩攻击等攻击方法都表现出良好的鲁棒性。
With the rapid development of the network technology, digital map products for the storage and application are even more extensive. As a new digital map product, remote sensing image map is widely used in the field of military mapping and geographic information navigation. How to protect copyright of remote sensing image map products has become a major research focus. Faced with this problem, people have proposed digital watermarking technology to protect the copyright of the products. Digital watermark technology loads the watermark such as text, binary image or a sequence of the number into the digital products by a particular way in order to protect the copyright. There are several problems in the remote sensing image map's watermarking algorithms:It is difficult to determine the location for embedding watermark, past approaches choose some positions in the pixels or the frequency domain of the map to embed the watermark directly. These approaches could have good effects in a few special cases of attacks, but are not versatile; The perturbation method of watermark doesn't have good performance. The perturbation method has a direct impact on the amount of the change in remote sensing image map's data; The characteristic of the remote sensing image map is not considered in the watermarking algorithms. Most watermarking algorithms are just designed using the data of the image.
To solve the above problems, combined with the remote sensing image map's characteristics, this dissertation presents a blind watermarking algorithm for copyright protection. The algorithm uses the stability of harris feature points and the characteristics of the wavelet multi-level to get the feature points on the field at all level of low frequency wavelet coefficient. The feature points are unified in the same dimension and classified into several clusters to get the representative points. Then a representative point of the cluster is selected to locate the reference point. The representative points got by this method are more relocatable. And this method enhances the robustness of the algorithm. At last the scrambled binary image information is embedded into the wavelet coefficient by the proposed perturbation method. The proposed perturbation method ensures the invisibility in maximum extent also improves the resistance to attacks. The invariance of the attribute data is considered in the extraction process. The proposed algorithm uses two methods to get the watermark. First method uses the geographical coordinates of the attribute data as a secret key to get watermark. While another way gets the watermark uses the embedding method as a reference. The proposed extraction method not only ensures the efficiency of the algorithm but also protects the integrity of the extracted watermark.
The experimental results show that the proposed algorithm has good performance of the invisibility and is effective against the geometric attack, filtering attack, noise attack, jpeg compression attack.
引文
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[3]Smith J.R, Comiskey B.O. Modulation and information hiding in images[C]. Proc. Int. Workshop Information Hiding, LNCS 1174,1996:207～226P.
[4]S.Craver, N.Memon, B.Yeo, M. Yeung. Can invisible watermarks resolve rightful ownerships[J]? IBM Research Report RC 20309,1996:158～167P.
[5]Su K, Kundur D, Hatzinakos D. Spatially localized image-dependent watermarking for statistical invisibility and collusion resistance[J]. IEEE Transactions on Multimedia, 2005:52～56P.
[6]Tsai H M, Chang L W. A high secure reversible visible watermarking scheme[C]. Proceedings of the 2007 IEEE International Conference on Multimedia and Expo,2007: 2106～2109P.
[7]Topkara M, Kamra A, Atallah M J, Cristina N R. ViWiD:Visible watermarking based defense against phishing[J]. Lecture Notes in Computer Science,2005:470～483P.
[8]Mohanty S P, Guturu P, Kougianos E, Pati N. A novel invisible color image watermarking scheme using image adaptive watermark creation and robust insertion-extraction[C]. ISM IEEE International Symposium on Multimedia,2006:153～160P.
[9]Maheshwari M, Arora R, Singh G. Invisible image watermarking using a public key algorithm[J]. Journal of the Institution of Engineers, Part CP:Computer Engineering Division,2006:27～31P.
[10]liu Quan, Jiang Xuemei. Design and realization of a meaningful digital watermarking algorithm based on RBF neural network[C]. International Conference on Neural Networks and Brain,2005:214～218P.
[11]Zhou Zude, Liu Quan, Jiang Xuemei. Researches on uniform meaningful watermark[C]. International Conference on Signal Processing,2002:128～132P.
[12]Huang Chunshang, Wu Jaling, Chen Dingyun. A blind watermarking algorithm with semantic meaningful watermarks[C]. Conference Record of the Thirty-Fourth Asilomar Conference on Signals, Systems and Computers,2000, Vol.2:1827～1830P.
[13]Wu Yongdong. On the security of an SVD-based ownership watermarking[J]. IEEE Transactions on Multimedia,2005,7(4):624～627P.
[14]Liu Yongliang, Wen Gao, Minghao Cui. General blind watermark schemes[C]. Second International Conference on Web Delivering of Music,2002, vol.2:143～149P.
[15]Wolfgang R B, Delp E J. Overview of image security techniques with applications in multimedia system[C]. Multimedia Networks:Security, Displays, Terminals, and Gateways,1997,3228:297～308P.
[16]Fleet D J. Embedding in visible images in color images[C]. In proceedings of IEEE Internet Conference on Image Processing, Piscataway:IEEE Press,1997,1:532～535P.
[17]D.Coltuc, Ph.Bolon, Watermarking by histogram specification[J]. Proceeding of SPIE, vol.657, Security and Watermarking of Multimedia Contents,1999:158～160P.
[18]Delaigie J.F, De Vleeschouwer D, Macq B. Low cost perceptive digital picture watermarking method[C]. Proc.ECMAST'97,1997:153～167P.
[19]Macq B., Delaigie J.F.De Vleeschouwer D., Digital watermarking[J]. Proc.SPIE 2659: Optical Security and Counterfeit Deterrence Technique,1996:99～110P.
[20]Kutter M. and Winkler S, A vision-based masking model for spread spectrum image watermarking[J], IEEE trans. Image Processing,2002,11(1):16～25P.
[21]Burgett S, Koch E, Zhao J. Copyright labeling of digitized image data[J].IEEE Communications Magazine,1998,36(3):94～100P.
[22]Cox I J, Killian J, et al. Secure spread spectrum watermarking for multimedia[J]. IEEE Transactions on Image Processing,1997,6(12):1673～1687P.
[23]Bors A.G., Pitas I., Embedding Parametric Digital Signatures in Images[C], Proceedings of European. Conference on Signal Processing,1996:252～257P.
[24]王树海,赵卫东等,一种鲁棒的自适应DCT域数字水印算法[J],微计算机信息,2008,24(18)：177-179页.
[25]廖晓峰,金渊智等,一种统计特性的数字水印算法[J],重庆大学学报,2009,32(8)：25-27页.
[26]李海燕,一种DCT域的彩色图像数字水印算法[J],合肥工业大学学报,2009,32(7)：1034-1036页.
[27]J.J.K.Ruanaidh, W.J.Dowling, and F.M.Boland, Phase watermarking of digital image[C], Proceedings of IEEE International Conference on Image Processing,1999:239-242P.
[28]O'ruanaidh J, Pun T.Rotation, Scale and translation invariant spread spectrum digital image watermarking[J]. Signal Processing,1998,66(3):303～317P.
[29]王志伟,朱长青等,一种基于DFT的DEM自适应数字水印算法[J],2010,15(5)：796-801页.
[30]王树梅,蔡键,一种基于DFT和曲线拟合的水印算法[J],2009,28(2)：66-69页.
[31]D.Kundur, and D.Hatzinakos, A robust digital image watermarking method using wavelet-based fusion[C], in Proceedings of IEEE ICIP'97, vol.1,1997:544～547P.
[32]刘彤,裘正定,小波域自适应图像水印算法研究[J],计算机学报,vo1.25,no.11,2002：.1195-1199页.
[33]H. J. Wang, P. C. Su, and C. C. J. Kuo, Wavelet-based digital image watermarking[J]. Opt. Exp., Dec.1998, vol3:491～496P.
[34]K. Byun, S. Lee, and H.Kim, A watermarking method using quantization and statistical characteristics of wavelet transform[J]. Proc. IEEE PDCAT,2005:689～693P.
[35]Wei-Hung Lin, Shi-Jinn Horng, Tzong-Wann Kao, PingzhiFan, Cheng-Ling Lee, and Yi Pan, An Efficient Watermarking Method Based on Significant Difference of Wavelet Coefficient Quantization[J], IEEE Transcation on multimedia,2008, Vol.10:163～167P.
[36]吕海翠,王丹等,小波变换的低频数字水印[J],计算机工程与应用,2009,45(11)：99-101页.
[37]何冰,赵杰等,基于DWT的抗RST攻击鲁棒性数字水印[J],计算机工程,2009,35(22)：134-136页.
[38]孙岩等,一种基于DWT和DCT相结合的彩色数字盲水印算法[J],计算机安全,2009(1)：65-67页.
[39]BarniM, BartoliniF, CaPPelliniV, et al. Near-lossless Digitial Watermarking for Copyright Protection of Remote Sensing Images[J]. International Geoscience and Remote Sensing Symposium(IGARSS)V3,2002:1447～1447P.
[40]Arto Kaarna, Pekka Toivanen, Digital Watermarking of Spectral Images in PCA/ Wavelet-transform Domain[C]. International Geoscience and Remote Sensing Symposium(IGARSS)V6,2003:3564～3567P.
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