General Tensor Discriminant Analysis and Gabor Features for Gait Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Reversibility improved lossless data hiding
Signal Processing
Reversible Data Hiding Based on Histogram
ICIC '07 Proceedings of the 3rd International Conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence
A reversible watermarking based on histogram shifting
IWDW'06 Proceedings of the 5th international conference on Digital Watermarking
IEEE Transactions on Circuits and Systems for Video Technology
Reliable embedding for robust reversible watermarking
ICIMCS '10 Proceedings of the Second International Conference on Internet Multimedia Computing and Service
Content-adaptive reliable robust lossless data embedding
Neurocomputing
Robust reversible watermarking scheme using Slantlet transform matrix
Journal of Systems and Software
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The histogram shifting based reversible watermarking techniques have attracted increasing interests due to their low computational complexity, high visual quality and considerable capacity. However, those methods suffer from unstable performance because they fail to consider the diversity of grayscale histograms for various images. For this purpose, we develop a novel histogram shifting based method by introducing a block statistical quantity (BSQ). The similarity of BSQ distributions for different images reduces the diversity of grayscale histograms and guarantees the stable performance of the proposed method. We also adopt different embedding schemes to prevent the issues of overflow and underflow. Moreover, by selecting the block size, the capacity of the proposed watermarking scheme becomes adjustable. The experimental results of performance comparisons with other existing methods are provided to demonstrate the superiority of the proposed method.