【摘要】 为解决数字水印算法的不可见性和鲁棒性问题,提出一种基于融合差分进化的粒子群算法的LWT-SVD域灰度图像数字水印优化算法.首先,利用提升小波变换(Lifting Wavelet Transform,LWT)对载体图像进行二级LWT分解,获得4个不同的子带.然后,对获得的每个子带分别进行奇异值分解(Singular Value Decomposition,SVD),并利用融合差分进化的粒子群算法对水印的嵌入阈值进行优化,分别获得对应于每个子带的最优的水印嵌入阈值.最后,将水印图像根据最优嵌入阈值嵌入到对应的载体图像的奇异值中.实验结果证明了与其他现有算法相比,提出的算法使得嵌入水印后的图像表现出较好的不可见性,并且在应对JPEG压缩、高斯噪声等常见的图像攻击方式时也表现出较好的鲁棒性.更多还原

【Abstract】 Aiming at the imperceptibility and robustness of digital watermarking algorithm,a LWTSVD domain optimization watermarking algorithm for gray image based on particle swarm optimization with differential evolution is proposed.Firstly,the carrier image is decomposed into 4 subbands by two levels LWT decomposition.Then,singular value decomposition(SVD)is performed for each subband.Meanwhile,the embedding strength of the watermark is optimized by using the particle swarm optimization with differential evolution,and the optimal embedding strength is obtained for each subband.Finally,the watermark image is embedded into the singular value of the corresponding carrier image according to the optimal embedding strength.Experimental results show that the proposed algorithm makes the imperceptibility of the watermarked image better,and shows better robustness when dealing with JPEG compression,noise and other common image attacks compared to other algorithms.更多还原