为了提高不同像素之间的相干性,基于最小化嵌入损失函数框架提出了一种空域图像自适应隐写算法。使用Daubechies小波构造滤波器预测载体图像的残差权重并获得损失值,利用均值滤波器对损失值进行平滑处理,结合校验格编码嵌入信息。使用两种不同的图像特征进行抗隐写分析,实验结果表明,当信息嵌入率较小时,所提算法的抗检测能力与HILL(Hill-pass,Low-pass,Low-pass)隐写算法的相近,且优于其他对比算法;当信息嵌入率较大时,所提算法的抗检测能力明显优于小波获得权重法、S-UNIWARD(Spatial-Universal Wavelet Relative Distortion)等主流隐写算法。

In order to improve the coherent among different pixels, a spatial image adaptive steganography algorithm is proposed based on the framework of minimizing the embedding distortion function. The Daubechies wavelet construction filter is used to predict the residual weight of cover and the cost value is obtained. A mean filter is used to smooth the cost value. The messages combined with syndrome trellis coding are embedded. Two different image features are used for anti-steganography analysis. Experimental results demonstrate that the anti-detection ability of the proposed algorithm is similar to the Hill-pass, Low-pass, Low-pass (HILL) steganography algorithm when the payload is small and is significantly better than the mainstream steganography algorithms such as wavelet obtained weights and spatial-universal wavelet relative distortion (S-UNIWARD ) when the payload is large.