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We compare two image bases with respect to their capabilities for image modeling and steganalysis. The first basis consists of wavelets, the second is a Laplacian pyramid. Both bases are used to decompose the image into subbands where the local dependency structure is modeled with a linear Bayesian estimator. Similar to existing approaches, the image model is used to predict coefficient values from...
Concatenated code is widely used in multimedia systems, such as DVB-T, ISDB-T and ATSC as terrestrial digital Television broadcasting standard of Europe, Japan and America, respectively. The concatenated code usually consists of Reed-Solomon code as outer code, Convolutional code as inner coder. The byte-level interleave also used to avoid burst errors in severe wireless channel. This class of concatenated...
Watermarked images are increasingly prevalent in the internet. Hence, any practical steganalyzer has to take the presence of watermarked images into account, particularly as potential source of false alarms due to similar embedding algorithms. In this study, we investigate the impact of watermarked images on the performance of a standard steganalyzer using two recent watermarking schemes: JPEG Compression...
Today, support vector machines (SVMs) seem to be the classifier of choice in blind steganalysis. This approach needs two steps: first, a training phase determines a separating hyperplane that distinguishes between cover and stego images; second, in a test phase the class membership of an unknown input image is detected using this hyperplane. As in all statistical classifiers, the number of training...
Most universal steganalysis techniques use an image model to reconstruct an estimate of the original, unmanipulated cover from the input. Differences between reconstructed and input images are an indication of a steganographic manipulation. In this paper, we analyze the relation between the modeling error of the image model and detection performance in the wavelet domain. Based on the modeling error...
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