Abstract
One of the open problems in lossless information hiding research is how to get adaptively better difference image architectures for given applications. In this paper we propose a simple and efficient approach to predict high-similar interpolation image from its sparse pattern and spectral expansion. After difference operator, peak value of the spike is very high. This method also provides a mathematic framework for evaluating de-correlating algorithm and can therefore be used to benchmark new algorithms. Finally, a proper reversible data hiding algorithm is also enclosed which refers conventional difference expansion principle. Overflow and underflow is considered in the fusion way. Simulations results demonstrate and verify that our new approach is much effective than local difference expansion method with good generalization performance.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
