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Xintao DUAN, Chun LI, Bingxin WEI, Guoming WU, Chuan QIN, Haewoon NAM. SCFformer: a binary data hiding method against JPEG compression based on spatial channel fusion Transformer[J]. Frontiers of Information Technology & Electronic Engineering, 1998, -1(-1): .
@article{title="SCFformer: a binary data hiding method against JPEG compression based on spatial channel fusion Transformer",
author="Xintao DUAN, Chun LI, Bingxin WEI, Guoming WU, Chuan QIN, Haewoon NAM",
journal="Frontiers of Information Technology & Electronic Engineering",
volume="-1",
number="-1",
pages="",
year="1998",
publisher="Zhejiang University Press & Springer",
doi="10.1631/FITEE.2300762"
}
%0 Journal Article
%T SCFformer: a binary data hiding method against JPEG compression based on spatial channel fusion Transformer
%A Xintao DUAN
%A Chun LI
%A Bingxin WEI
%A Guoming WU
%A Chuan QIN
%A Haewoon NAM
%J Journal of Zhejiang University SCIENCE C
%V -1
%N -1
%P
%@ 2095-9184
%D 1998
%I Zhejiang University Press & Springer
%DOI 10.1631/FITEE.2300762
TY - JOUR
T1 - SCFformer: a binary data hiding method against JPEG compression based on spatial channel fusion Transformer
A1 - Xintao DUAN
A1 - Chun LI
A1 - Bingxin WEI
A1 - Guoming WU
A1 - Chuan QIN
A1 - Haewoon NAM
J0 - Journal of Zhejiang University Science C
VL - -1
IS - -1
SP -
EP -
%@ 2095-9184
Y1 - 1998
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/FITEE.2300762
Abstract: To enhance information security during transmission over public channels, images are frequently employed for binary data hiding. Nonetheless, this data is vulnerable to distortion due to JPEG compression, leading to challenges in recovering the original binary data. Addressing this issue, this paper introduces a pioneering method for binary data hiding that leverages a combined spatial and channel attention Transformer, termed SCFformer, designed to withstand JPEG compression. This method employs a novel DCT quantization truncation mechanism during the hiding phase to bolster the stego image’s resistance to JPEG compression, utilizing spatial and channel attention to conceal information in less perceptible areas and thereby enhancing the model’s resistance to steganalysis. In the extraction phase, the DCT quantization stage mechanism minimizes secret image loss during compression, facilitating easier information retrieval. The incorporation of scalable modules adds flexibility, allowing for variable-capacity data hiding. Experimental findings validate the high security, large capacity, and flexibility of our scheme, alongside a marked improvement in binary data recovery post-JPEG compression, underscoring our method’s leading-edge performance.
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