Efficient JPEG Steganography Using Domain Transformation of Embedding Entropy
Autor: | Jiangqun Ni, Yun Q. Shi, Xianglei Hu |
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Rok vydání: | 2018 |
Předmět: |
Domain transformation
Steganography Computer science business.industry Applied Mathematics Jpeg steganography 020207 software engineering Pattern recognition 02 engineering and technology computer.file_format JPEG Distortion Signal Processing 0202 electrical engineering electronic engineering information engineering Discrete cosine transform Entropy (information theory) Embedding 020201 artificial intelligence & image processing Artificial intelligence Electrical and Electronic Engineering business computer |
Zdroj: | IEEE Signal Processing Letters. 25:773-777 |
ISSN: | 1558-2361 1070-9908 |
DOI: | 10.1109/lsp.2018.2818674 |
Popis: | Nowadays, JPEG steganographic schemes, e.g., J-UNIWARD, which take into account the effects of embedding in the spatial domain tend to exhibit higher security and introduce less artifacts that can be captured by the prevalent steganalyzers. Following the paradigm, this letter proposes a new design of the distortion measure for JPEG steganography by incorporating the statistics of both the spatial and discrete cosine transform (DCT) domains. The spatial statistics of the decompressed JPEG images are first well characterized with distortion measures of some efficient steganographic schemes in the spatial domain, e.g., HILL, and the resulting embedding entropies of spatial blocks in alignment with DCT blocks are then transformed into the DCT domain to obtain the distortion measures for JPEG steganography. Experimental results show that the proposed method outperforms considerably other state-of-the-art JPEG steganographic schemes, i.e., J-UNIWARD and UERD, for the most effective feature set GFR at present, and rivals them for other feature sets, e.g., DCTR and CC-JRM. |
Databáze: | OpenAIRE |
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