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- W2938154516 abstract "Embedding costs used in content-adaptive image steganographic schemes can be defined in a heuristic way or with a statistical model. Inspired by previous steganographic methods, i.e., MG (multivariate Gaussian model) and MiPOD (minimizing the power of optimal detector), we propose a model-driven scheme in this paper. Firstly, we model image residuals obtained by high-pass filtering with quantized multivariate Gaussian distribution. Then, we derive the approximated Fisher Information (FI). We show that FI is related to both Gaussian variance and filter coefficients. Lastly, by selecting the maximum FI value derived with various filters as the final FI, we obtain embedding costs. Experimental results show that the proposed scheme is comparable to existing steganographic methods in resisting steganalysis equipped with rich models and selection-channel-aware rich models. It is also computational efficient when compared to MiPOD, which is the state-of-the-art model-driven method." @default.
- W2938154516 created "2019-04-25" @default.
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- W2938154516 date "2019-05-01" @default.
- W2938154516 modified "2023-10-16" @default.
- W2938154516 title "A New Spatial Steganographic Scheme by Modeling Image Residuals with Multivariate Gaussian Model" @default.
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- W2938154516 doi "https://doi.org/10.1109/icassp.2019.8682688" @default.
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