Reversible Data Hiding in Encrypted Images Based on Adaptive Gradient Prediction

Abstract

The existing reversible data hiding (RDH) technology solves the problem that the ciphertext data and carrier are easily damaged in the traditional scheme, which has become a research hotspot in information hiding. However, because of the small coverage area of the predictor and poor prediction ability of the existing reversible data hiding in encrypted images (RDH-EI) technology based on pixel predictor, the embedding performance of the algorithm is limited. Therefore, this paper proposes an adaptive gradient prediction (AGP) scheme. The AGP employs a comprehensive and efficient local complexity measurement strategy to make predictions based on pixel changes around the predicted pixel, including horizontal, vertical, and diagonal directions. The experimental results show that the AGP-RDHEI scheme has apparent advantages in embedding rate.