Abstract-In the intra-frame coding of H.264/AVC, information hiding can be implemented by modulating the prediction modes of 4×4 luminance blocks. Since this kind of method has characteristics of high speed, good concealment and so on, it has become a great security threat. Therefore, it is necessary to study the steganalysis method. In this paper, we first analyzed the changes of remarkable characteristics in intra-frame coding caused by modulating intra prediction modes for information hiding. We found that the correlation among the prediction modes in different 4×4 luminance blocks, belonging to an intra-frame coding macroblock, was changed. According to this, we have designed statistical models to make quantitative extraction of these correlation characteristics. And a steganography detector was constructed based on the support vector machine. The experimental results show that the steganography detector constructed in this paper can achieve a detection accuracy of more than 90% when the embedding rate is larger than 25%.
In this work we study the methods for reconstructing spectral reflectances of images. To reproduce the spectral reflectance more accurately and the colours more realistically, we obtain a so-called average transformation matrix, using a series of different modulated light sources to illuminate a standard whiteboard. For eliminating the influence of those light sources on RGB images, we first use a white-balance algorithm to standardize the scene information, thus obtaining a uniform RGB image with different sources. Then we map the RGB image onto the spectral reflectance basing on a compressive sensing algorithm and the principal component analysis and, finally, reconstruct the spectral reflectance of the testing sample. We compare the reconstruction accuracies of our compressive sensing algorithm based on white-balance calibration with the results derived using a pseudo-inverse method and a traditional compressive sensing algorithm. Our simulation results show that, under the same conditions of reconstruction, the residual errors and the colour difference resulting from our improved algorithm are less than those produced by the other two algorithms. In other words, the reconstruction algorithm suggested by us outperforms the other methods and can provide better performance of image colour reproduction.
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