Exploiting Fine-Grained DCT Representations for Hiding Image-Level
  Messages within JPEG Images
Junxue Yang Xin Liao
Unlike hiding bit-level messages, hiding image-level messages is more
challenging, which requires large capacity, high imperceptibility, and high
security. Although recent advances in hiding image-level messages have been
remarkable, existing schemes are limited to lossless spatial images as covers
and cannot be directly applied to JPEG images, the ubiquitous lossy format
images in daily life. The difficulties of migration are caused by the lack of
targeted design and the loss of details due to lossy decompression and
re-compression. Considering that taking DCT densely on $8\times8$ image patches
is the core of the JPEG compression standard, we design a novel model called
\textsf{EFDR}, which can comprehensively \underline{E}xploit
\underline{F}ine-grained \underline{D}CT \underline{R}epresentations and embed
the secret image into quantized DCT coefficients to avoid the lossy process.
Specifically, we transform the JPEG cover image and hidden secret image into
fine-grained DCT representations that compact the frequency and are associated
with the inter-block and intra-block correlations. Subsequently, the
fine-grained DCT representations are further enhanced by a sub-band features
enhancement module. Afterward, a transformer-based invertibility module is
designed to fuse enhanced sub-band features. Such a design enables a
fine-grained self-attention on each sub-band and captures long-range
dependencies while maintaining excellent reversibility for hiding and recovery.
To our best knowledge, this is the first attempt to embed a color image of
equal size in a color JPEG image. Extensive experiments demonstrate the
effectiveness of our \textsf{EFDR} with superior performance.