地球信息科学学报 ›› 2021, Vol. 23 ›› Issue (10): 1882-1891.doi: 10.12082/dqxxkx.2021.210021

• 遥感科学与应用技术 • 上一篇    

结合ASIFT和归一化的抗仿射变换遥感影像盲水印算法

秦如贞1,2,3(), 张黎明1,2,3,*(), 伍庭晨1, 李玉1,2,3, 王昊1,2,3   

  1. 1.兰州交通大学测绘与地理信息学院,兰州 730070
    2.地理国情监测技术应用国家地方联合工程研究中心,兰州 730070
    3.甘肃省地理国情监测工程实验室,兰州 730070
  • 收稿日期:2021-01-15 修回日期:2021-04-10 出版日期:2021-10-25 发布日期:2021-12-25
  • 通讯作者: * 张黎明(1975— ),男,甘肃天水人,博士,教授,主要从事地理信息安全,空间数据安全,版权保护,地图数据数字水印的理论与方法等研究。E-mail: zhang_lm@163.com
  • 作者简介:秦如贞(1997— ),女,山西吕梁人,硕士生,主要从事遥感影像版权保护研究。E-mail: 1043020927@qq.com
  • 基金资助:
    甘肃高等学校产业支撑引导项目项目(2019C-04);国家自然科学基金项目(41761080);兰州交通大学优秀平台支持(201806)

A Blind Watermarking Algorithm for Remote Sensing Image based on Anti-Affine Transforma-tion Combining ASIFT and Normalization

QIN Ruzhen1,2,3(), ZHANG Liming1,2,3,*(), WU Tingchen1, LI Yu1,2,3, WANG Hao1,2,3   

  1. 1. Faculty of Geomatics, Lanzhou Jiaotong University, Lanzhou 730070, China
    2. National-Local Joint Engineering Research Center of Technologies and Applications for National Geographic State Monitoring, Lanzhou 730070, China
    3. Gansu Provincial Engineering Laboratory for National Geographic State Monitoring, Lanzhou 730070, China
  • Received:2021-01-15 Revised:2021-04-10 Online:2021-10-25 Published:2021-12-25
  • Contact: ZHANG Liming
  • Supported by:
    Industrial Support and Guidance Projects of Colleges and Universities in Gansu(2019C-04);National Natural Science Foundation of China(41761080);Lanzhou Jiaotong University Excellent Platform(201806)

摘要:

针对遥感影像使用过程中,含水印影像经过仿射变换后水印与影像的同步性被破坏,导致水印无法正常检测的问题,本文提出了一种适用于遥感影像的抗仿射变换盲水印算法。首先通过ASIFT算法提取影像具有仿射不变性的特征点,根据特征尺度的大小与特征点间的欧式距离筛选适量特征点,构造对应的正方形特征区域;然后通过计算特征区域的仿射不变矩得出归一化变换函数的参数,对特征区域进行归一化处理,并以归一化特征区域的不变质心为中心提取子区域作为水印嵌入区域,对该区域进行二级离散小波变换,得到水印嵌入区域的低频信息;运用量化嵌入规则将水印嵌入到低频信息中,依次进行低频信息逆小波变换,水印嵌入前后特征区域差值图像反归一化,最后将反归一化差值图像叠加在原始影像特征区域上,完成水印的嵌入。实验选用了3000像素×3000像素的高分二号遥感影像作为载体影像,含版权信息的二值图像作为水印,实验表明:含水印的遥感影像经过旋转、平移、缩放在内的仿射变换后,仍能准确提取水印信息;算法可有效抵抗加噪、滤波、裁剪等常规水印攻击,攻击后影像提取的水印与原水印相关系数均高于0.9;水印具有良好不可感知性;在水印提取时无需原始遥感影像,属于盲水印算法。

关键词: 遥感影像, 仿射变换, 数字水印, ASIFT, 不变矩, 特征尺度, 归一化, 特征区域

Abstract:

In the process of using remote sensing images, the synchronization between watermark and remote sensing image is disrupted after affine transformation is performed on the watermarked image. Although the watermark is not removed after affine transformation, the size and relative position of the image are changed, which leads to the problem that watermark cannot be detected correctly. It is significant to improve the robustness of digital watermarking. This paper proposes a blind watermarking algorithm for remote sensing image, which can effectively resist affine transformation. Firstly, the affine invariant feature points of the image are extracted by ASIFT algorithm. The stable, evenly distributed, appropriate feature points are selected according to the size of the feature scale and the Euclidean distance between the feature points to construct the corresponding square feature regions. Secondly, take a feature region as an example, the affine invariant moments of the feature region are calculated to normalize the feature region. With the invariant centroid of the normalized feature region as the center, the sub region is extracted as watermark embedding region. The low-frequency information of the watermark embedding region is obtained by two-level wavelet transform. The watermark is embedded into the low-frequency information using the quantization embedding rule to complete the watermark embedding. Finally, inverse wavelet transform of low-frequency information is performed. The difference image of the characteristic region before and after embedding is denormalized. The denormalized difference image is superimposed on the original image characteristic region to complete the watermark embedding. In this paper, a GF-2 remote sensing image of 3000 × 3000 pixels was used as the carrier image, while the binary image with copyright information was used as the watermark. This paper measured the invisibility of the watermark by calculating the magnitude of the peak signal-to-noise ratio. In the robustness testing experiments, the watermarked image was subjected to affine transformation, noise adding attack, and filtering attack. Then, the algorithm of this paper was used for watermark extraction. The watermark with the highest normalized correlation value extracted was selected for robustness evaluation. The experiment results show that, after affine transformation, including rotation, translation, and scaling, the watermark information was accurately extracted from the watermarked remote sensing image through the algorithm. The algorithm is robust to noise, filtering, cropping, and other conventional watermarking attacks. The watermark has good imperceptibility. ASIFT is a blind watermarking algorithm. The watermark detection process does not need the original remote sensing image. Our algorithm has strong practicability.

Key words: remote sensing image, affine transformation, digital watermarking, ASIFT, invariant moments, feature scale, normalization, feature region