基于小波对比度和神经网络的图像隐写方法

为使通信安全在传输过程中提供较大的秘密信息嵌入量，并保持较好的载密图像质量，提出一种基于自组织特征映射神经网络和小波对比度的图像隐写方法。将载体图像分成固定大小的小块，采用小波一级分解并计算其小波对比度，利用自组织特征映射神经网络将小块分为3类，采用模算子技术嵌入秘密信息。实验结果表明，该方法有较大的嵌入量并保持良好的载密图像质量。

Image Steganographic Method Based on Wavelet Contrast and Neural Networks

To provide larger capacity of the hidden secret data and to maintain a better visual quality of stego-image, this paper presents a image steganographic method based on Self-Organizing feature Map(SOM) neural networks and wavelet contrast. It divides an image into blocks, and decomposes every block into one-level wavelet to obtain the wavelet contrast. The method classifies blocks into 3 kindsby SOM, and embeds secret information with steganography, which is based on modulus. Experimental results show that the proposed method hides much more information and maintains a better visual quality of stego-image.