Comparative assessment of PEE methods and new performance measurement for RDH

Abstract

The paper mainly analyzes four typical reversible data hiding (RDH) algorithms that use PEE technology in combination: Conventional Prediction-error-expansion(C-PEE), Adaptive Prediction-error-expansion(A-PEE), Pairwise Prediction-error-expansion (P-PEE), Improve Pairwise Prediction-error-expansion(IP-PEE). And the experimental comparison results are also given. In addition, in the research process, we found that the peak signal-to-noise ratio (PSNR) and embedding capacity (EC) of many algorithms are very close, due to lack of benchmark tools for technical evaluation in the RDH field, thus this paper proposes a new performance measurement method based on the PSNR and EC measurement, we call it the prediction error accuracy rate, Determined by the ratio of the capacity that meets the embedding conditions to the total capacity of the image, combined with the measurement of this method, can better determine whether the performance of the algorithm is optimal. Finally, in this area, challenge and future directions are also given.