148 research outputs found
A contrast-sensitive reversible visible image watermarking technique
A reversible (also called lossless, distortion-free, or
invertible) visible watermarking scheme is proposed to satisfy the applications, in which the visible watermark is expected to combat copyright piracy but can be removed to losslessly recover the original image. We transparently reveal the watermark image by overlapping it on a user-specified region of the host image through adaptively adjusting the pixel values beneath the watermark, depending on the human visual system-based scaling factors. In order to achieve reversibility, a reconstruction/ recovery packet, which is utilized to restore the watermarked area, is reversibly inserted into non-visibly-watermarked region. The packet is established according to the difference image between the original image and its approximate version instead of its visibly watermarked version so as to alleviate its overhead. For the generation of the approximation, we develop a simple prediction technique that makes use of the unaltered neighboring pixels as auxiliary information. The recovery packet is uniquely encoded before hiding so that the original watermark pattern can be reconstructed based on the encoded packet. In this way, the image recovery process is carried out without needing the availability of the watermark. In addition, our method adopts data compression for further reduction in the recovery packet size and improvement in embedding capacity. The experimental results demonstrate the superiority of the proposed scheme compared to the existing methods
Vector-based Efficient Data Hiding in Encrypted Images via Multi-MSB Replacement
As an essential technique for data privacy protection, reversible data hiding
in encrypted images (RDHEI) methods have drawn intensive research interest in
recent years. In response to the increasing demand for protecting data privacy,
novel methods that perform RDHEI are continually being developed. We propose
two effective multi-MSB (most significant bit) replacement-based approaches
that yield comparably high data embedding capacity, improve overall processing
speed, and enhance reconstructed images' quality. Our first method, Efficient
Multi-MSB Replacement-RDHEI (EMR-RDHEI), obtains higher data embedding rates
(DERs, also known as payloads) and better visual quality in reconstructed
images when compared with many other state-of-the-art methods. Our second
method, Lossless Multi-MSB Replacement-RDHEI (LMR-RDHEI), can losslessly
recover original images after an information embedding process is performed. To
verify the accuracy of our methods, we compared them with other recent RDHEI
techniques and performed extensive experiments using the widely accepted BOWS-2
dataset. Our experimental results showed that the DER of our EMR-RDHEI method
ranged from 1.2087 bit per pixel (bpp) to 6.2682 bpp with an average of 3.2457
bpp. For the LMR-RDHEI method, the average DER was 2.5325 bpp, with a range
between 0.2129 bpp and 6.0168 bpp. Our results demonstrate that these methods
outperform many other state-of-the-art RDHEI algorithms. Additionally, the
multi-MSB replacement-based approach provides a clean design and efficient
vectorized implementation.Comment: 14 pages; journa
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