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