A DCT-domain system for robust image watermarking
Signal Processing
JPEG Still Image Data Compression Standard
JPEG Still Image Data Compression Standard
Lossless data embedding--new paradigm in digital watermarking
EURASIP Journal on Applied Signal Processing - Emerging applications of multimedia data hiding
Glicbawls?? Grey Level Image Compression by Adaptive Weighted Least Squares
DCC '01 Proceedings of the Data Compression Conference
An Improved Reversible Difference Expansion Watermarking Algorithm
IWDW '07 Proceedings of the 6th International Workshop on Digital Watermarking
Reversible watermarking algorithm using sorting and prediction
IEEE Transactions on Circuits and Systems for Video Technology
Reversible Image Watermarking Based on Integer-to-Integer Wavelet Transform
IEEE Transactions on Information Forensics and Security - Part 1
IEEE Transactions on Multimedia
The LOCO-I lossless image compression algorithm: principles and standardization into JPEG-LS
IEEE Transactions on Image Processing
Edge-directed prediction for lossless compression of natural images
IEEE Transactions on Image Processing
Lossless generalized-LSB data embedding
IEEE Transactions on Image Processing
Reversible data embedding into images using wavelet techniques and sorting
IEEE Transactions on Image Processing
Expansion Embedding Techniques for Reversible Watermarking
IEEE Transactions on Image Processing
Reversible data embedding using a difference expansion
IEEE Transactions on Circuits and Systems for Video Technology
Hierarchy-based reversible data hiding
Expert Systems with Applications: An International Journal
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In this paper, we present a reversible data embedding scheme based on an adaptive edge-directed prediction for images. It is known that the difference expansion is an efficient data embedding method. Since the expansion on a large difference will cause a significant embedding distortion, a location map is usually employed to select small differences for expansion and to avoid overflow/underflow problems caused by expansion. However, location map bits lower payload capacity for data embedding. To reduce the location map, our proposed scheme aims to predict small prediction errors for expansion by using an edge detector. Moreover, to generate a small prediction error for each pixel, an adaptive edge-directed prediction is employed which adapts reasonably well between smooth regions and edge areas. Experimental results show that our proposed data embedding scheme for natural images can achieve a high embedding capacity while keeping the embedding distortion low.