Steganography using Gabor filter and anisotropic diffusion

In order to improve the statistical security and the ability of resistance to steganalysis of adaptive steganography, an adaptive steganography algorithm based on Gabor filters and anisotropic diffusion is proposed, which can be utilized in an arbitrary domain. Compared with other adaptive embedding schemes, this method can define image distortion more accurately. Firstly, Gabor filters with multi-orientation and multi-scale is employed to determine the noisy regions or textures of cover image. Then the P-M anisotropic diffusion model is utilized to make image elements with low distortion cost relatively cluster in complex areas of image, and better retain the image edge information. At last, the syndrome-trellis codes is used to realize the actual embedding method to minimize the expected distortion for a given payload. The experimental results illustrate that the proposed method can significantly improve the accuracy of embedding in noisy regions and textures, and gains a better performance on resisting the current state-of-the-art steganalysis over prior algorithms.

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