Journal ArticleDOI
Lossless generalized-LSB data embedding
TLDR
In this paper, a generalization of the well-known least significant bit (LSB) modification is proposed as the data-embedding method, which introduces additional operating points on the capacity-distortion curve.Abstract:
We present a novel lossless (reversible) data-embedding technique, which enables the exact recovery of the original host signal upon extraction of the embedded information. A generalization of the well-known least significant bit (LSB) modification is proposed as the data-embedding method, which introduces additional operating points on the capacity-distortion curve. Lossless recovery of the original is achieved by compressing portions of the signal that are susceptible to embedding distortion and transmitting these compressed descriptions as a part of the embedded payload. A prediction-based conditional entropy coder which utilizes unaltered portions of the host signal as side-information improves the compression efficiency and, thus, the lossless data-embedding capacity.read more
Citations
More filters
Book
Digital Watermarking and Steganography
TL;DR: This new edition now contains essential information on steganalysis and steganography, and digital watermark embedding is given a complete update with new processes and applications.
Journal ArticleDOI
Expansion Embedding Techniques for Reversible Watermarking
D.M. Thodi,Jeffrey J. Rodriguez +1 more
TL;DR: The experimental results for many standard test images show that prediction-error expansion doubles the maximum embedding capacity when compared to difference expansion, and there is a significant improvement in the quality of the watermarked image, especially at moderate embedding capacities.
Journal ArticleDOI
Reversible Data Hiding in Encrypted Image
TL;DR: This work proposes a novel reversible data hiding scheme for encrypted image, where the additional data can be embedded into the image by modifying a small proportion of encrypted data.
Journal ArticleDOI
Separable Reversible Data Hiding in Encrypted Image
TL;DR: This work proposes a novel scheme for separable reversible data hiding in encrypted images by exploiting the spatial correlation in natural image when the amount of additional data is not too large.
Journal ArticleDOI
An Improved Reversible Data Hiding in Encrypted Images Using Side Match
TL;DR: This letter adopts a better scheme for measuring the smoothness of blocks, and uses the side-match scheme to further decrease the error rate of extracted-bits in an improved version of Zhang's reversible data hiding method in encrypted images.
References
More filters
Journal ArticleDOI
Arithmetic coding for data compression
TL;DR: The state of the art in data compression is arithmetic coding, not the better-known Huffman method, which gives greater compression, is faster for adaptive models, and clearly separates the model from the channel encoding.
Journal ArticleDOI
Reversible data embedding using a difference expansion
TL;DR: The redundancy in digital images is explored to achieve very high embedding capacity, and keep the distortion low, in a novel reversible data-embedding method for digital images.
Journal ArticleDOI
The LOCO-I lossless image compression algorithm: principles and standardization into JPEG-LS
TL;DR: LOCO-I as discussed by the authors is a low complexity projection of the universal context modeling paradigm, matching its modeling unit to a simple coding unit, which is based on a simple fixed context model, which approaches the capability of more complex universal techniques for capturing high-order dependencies.
Journal ArticleDOI
Multimedia watermarking techniques
Frank Hartung,Martin Kutter +1 more
TL;DR: The basic concepts of watermarking systems are outlined and illustrated with proposed water marking methods for images, video, audio, text documents, and other media.
Journal ArticleDOI
Context-based, adaptive, lossless image coding
Xiaolin Wu,Nasir Memon +1 more
TL;DR: The CALIC obtains higher lossless compression of continuous-tone images than other lossless image coding techniques in the literature and can afford a large number of modeling contexts without suffering from the context dilution problem of insufficient counting statistics as in the latter approach.