  Recently, with the introduction of JPEG phase-aware steganalysis features,
e.g., GFR, the design of JPEG steganographic distortion cost function turns to
maintain not only the statistical undetectability in DCT domain but also in
spatial domain. To tackle this issue, this paper presents a novel paradigm for
the design of JPEG steganographic distortion cost function, which calculates
the distortion cost via a generalized Distortion Cost Domain Transformation
(DCDT) function. The proposed function comprises the decompressed pixel block
embedding changes and their corresponding embedding distortion costs for unit
change, where the pixel embedding distortion costs are represented in a more
general exponential model, aiming to flexibly allocate the embedding data. In
this way, the JPEG steganography could be formulated as the optimization
problem of minimizing the overall distortion cost in its decompressed spatial
domain, which is equivalent to maximizing its statistical undetectability
against JPEG phase-aware steganalysis features. Experimental results show that
the proposed DCDT equipped with HiLL (a spatial steganographic distortion cost
function) is superior to other state-of-the-art JPEG steganographic schemes,
e.g., UERD, J-UNIWARD, and GUED in resisting the detection of JPEG phase-aware
feature-based steganalyzers GFR and SCA-GFR, and rivals BET-HiLL with one order
of magnitude lower computational complexity, along with the possibility of
being further improved by considering the mutually dependent embedding
interactions. In addition, the proposed DCDT is also verified to be effective
for different image databases and quality factors.
