1,631 research outputs found
Reversible Embedding to Covers Full of Boundaries
In reversible data embedding, to avoid overflow and underflow problem, before
data embedding, boundary pixels are recorded as side information, which may be
losslessly compressed. The existing algorithms often assume that a natural
image has little boundary pixels so that the size of side information is small.
Accordingly, a relatively high pure payload could be achieved. However, there
actually may exist a lot of boundary pixels in a natural image, implying that,
the size of side information could be very large. Therefore, when to directly
use the existing algorithms, the pure embedding capacity may be not sufficient.
In order to address this problem, in this paper, we present a new and efficient
framework to reversible data embedding in images that have lots of boundary
pixels. The core idea is to losslessly preprocess boundary pixels so that it
can significantly reduce the side information. Experimental results have shown
the superiority and applicability of our work
Reversible data hiding in JPEG images based on adjustable padding
In this paper, we propose a reversible data hiding scheme that enables an adjustable amount of information to be embedded in JPEG images based on padding strategy. The proposed embedding algorithm only modifies, in a subtle manner, an adjustable number of zero-valued quantised DCT coefficients to embed the message. Hence, compared with a state-of-the-art based on histogram shifting, the proposed scheme has a relatively low distortion to the host images. In addition to this, we found that by representing the message in ternary instead of in binary, we can embed a greater amount of information while the level of distortion remains unchanged. Experimental results support that the proposed scheme can achieve better visual quality of the marked JPEG image than the histogram shifting based scheme. The proposed scheme also outperforms this state-of-the-art in terms of the ease of implementation
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