基于IWT-SVD和BRISK的鲁棒图像水印算法

目的 针对数字图像水印中传统奇异值分解算法存在的提取水印对角线失真和目前的特征点匹配算法速度慢引起抗组合几何攻击性能弱问题，提出基于IWT-SVD和BRISK的鲁棒图像水印算法。方法 该方案是将Logistics混沌映射置乱的水印嵌入宿主图像IWT变换后进行SVD分解的矩阵中，然后运用BRISK算法完成失真图像的几何校正，最后根据提取的水印图像特性，用邻域平均法进行对角线元素修正。结果 嵌入水印后PSNR高于42 dB，在各种常规信号处理和组合几何攻击下，NC平均值在0.95以上，提取出的水印对角线失真问题得到明显改善。结论 实验结果表明，该方案能提高图像特征点的匹配速度，性能得到增强，水印不可见性较好，进一步提升了图像的鲁棒性。

Robust Image Watermarking Algorithm Based on IWT-SVD and BRISK

The work aims to propose a robust image watermarking algorithm based on IWT-SVD and BRISK to solve the problems of the traditional singular value decomposition algorithm in digital image watermarking, such as diagonal distortion of extracted watermark and the weak performance against combined geometric attacks caused by slow speed of the current feature point matching algorithm. In this scheme, the watermark scrambled by the chaotic map was em-bedded into the singular value matrix of the SVD decomposition after IWT transformation of the host image, and then the BRISK (Binary Robust Invariant Scalable Keypoints) algorithm was used to complete the geometric correction of the distorted image. Finally, according to the extracted watermark image characteristics, the diagonal element correction was performed by the neighborhood averaging method. After the watermark was embedded, the PSNR was higher than 42 dB. Under various conventional signal processing and combined geometric attacks, the normalized correlation values of the extracted watermark and the original watermark were above 0.95, and the diagonal distortion of extracted watermark was significantly improved. Experimental results show that the scheme can increase the matching speed of image feature points, enhance the performance, provide better invisible watermark, and further improve the robustness of image.