Reversible data hiding: A contemporary survey of state-of-the-art, opportunities and challenges

作者:Sanjay Kumar, Anjana Gupta, Gurjit Singh Walia

摘要

The goal of this survey is to review the state-of-the art Reversible Data Hiding (RDH) methods, classify these methods into different classes, and list out new trends in this field. RDH, in general, is a challenging problem and has potential applications in the today’s digital world. Reversible data hiding methods not only securely transfer secret data but also recover the cover media faithfully. Recently, RDH methods are mainly focused on obtaining high capacity along with tuneable quality. Although, extensive investigations in the field of reversible data hiding was carried out in the recent past, a comprehensive review of existing literature for listing out research gap and future directions has not yet been reported. In this survey, we have classified the reversible data hiding methods mainly into a) Plain domain b) Encrypted domain and also examine their pro and cons. Tabular comparison of various RDH methods has been provided considering various design and analysis aspects. Moreover, we discuss important issues related to reversible data hiding and use of benchmarked datasets along with performance metrics for evaluation of RDH methods.

论文关键词:Data hiding, Lossless compression, Reversible data hiding, Histogram shifting, Difference expansion, Prediction error

论文评审过程:

论文官网地址:https://doi.org/10.1007/s10489-021-02789-2