针对信息安全领域隐写技术存在的感知失真过大和图像源压缩率高造成误差率高的问题, 设计了一种基于Karhunen-Loeve transform (KLT)优化的图像隐写术。通过迭代聚类算法求解协方差矩阵与聚类平均值,对相关数值 进行调整分割图像,引入KLT算法压缩图像数据,用最低有效位代替加密数据来隐藏数据,提 取信息时采用反向线性变换运算及原始像素矩阵获得有效的隐藏图像信息。结果表明,与常用 算法相比该方法提取的图像有较高容量、较大信噪比及较小数据失真。

Aiming at the problem of too much perceptual distortion and high error rates caused by high image source compression rate existing in steganography technology of information security field, an image steganography based on Karhunen-Loeve transform (KLT) optimization technique is designed. The covariance matrix and cluster mean value are obtained with iterative clustering algorithm. It divides images by adjusting the correlation values. The image data are compressed by introducing KLT algorithm. The least significant bit is adopted to hide data instead of the encrypting data. Image informations are hidden effectively by using inverse linear transformation operations and the original pixel matrix when extracting informations. Results show that image extracted by the method has higher capacity, larger signal-to-noise ratio and smaller image data distortion compared with common algorithms.