基于灰狼优化边缘检测和XOR编码的图像自适应隐写算法

Adaptive image steganography algorithm based on grey wolf optimized edge detection and XOR coding

基于人眼视觉感知特性,提出了一种新型的边缘检测和XOR编码相结合的图像自适应隐写算法。通过设计基于灰狼优化(grey wolf optimization,GWO)算法的边缘检测,根据秘密信息的大小自适应地调整边缘检测阈值,利用粒子群优化(particle swarm optimization,PSO)算法优化边缘和非边缘像素的嵌入位数,结合XOR编码实现对混沌加密后的秘密信息的嵌入。实验结果表明,该隐写算法比现有文献算法具有更大的隐写容量,能较好地保持载密图像的不可感知性,并已通过像素差值直方图(pixel difference histogram,PDH)安全性分析。

An image adaptive steganography was proposed using combination between grey wolf optimizer-based edge detection and XOR coding.The algorithm firstly adjusted the threshold of edge detection by the design of GWO-based edge detection and the capacity of messages.Next,it optimized the number of bits in edge points and non-edge points with particle swarm optimization(PSO).Finally,confidential information after chaos encryption was embedded according to the optimal results in the above with XOR coding.The experiment shows that the proposed algorithm has greater capacity of messages for embedding than existing algorithms while maintaining a relatively good imperceptibility with the ability to pass pixel difference histogram(PHD)security analysis.