An adaptive pixel value ordering based reversible data hiding scheme for images

Abstract

Pixel value ordering (PVO) is a prominent method for reversible data hiding, which has gained increasing research interest in recent years due to its effective performance producing high-fidelity marked images. PVO-based methods performance lies on block dimensions and thresholds for classification. However, most methods determine proper parameters by performing exhaustive searches in restricted search spaces. In this paper, we present a novel Pixel Value Ordering technique based on Genetic Algorithms (PVO-GA) to address these issues. PVO-GA uses flexible sized blocks to take advantage of different block features, to better exploit image redundancy. A genetic algorithm is introduced to optimize the embedding process since the solutions space is greatly expanded. Results showed that PVO-GA achieves satisfactory levels in terms of the introduced distortion while significantly reduces the computational cost needed to find the optimal set of insertion parameters when compared to previous methods.