Non-local PPVO-based reversible data hiding using opposite direction pairwise embedding

Abstract

In recent years, pixel-value-ordering (PVO) has become a frequently used framework in which researchers have developed many novel reversible data hiding (RDH) methods. Aiming at enlarging the embedding capacity, the well-known pixel-based PVO (PPVO) was proposed. In PPVO, each pixel is predicted by a block of context pixels in its local region and the context size is fixed for each round of embedding, which makes it difficult to perform effectively for pixels located in textured regions. In this paper, firstly, we propose to acquire context pixels from the whole cover image to realize a non-local PPVO, which is implemented on a one-dimensional global sorted array obtained by our newly designed quadruple layer predictor. With the proposed predictor that has a high accuracy, the contexts used for PPVO prediction become smoother, facilitating to achieve a better performance. Secondly, by utilizing the one-dimensional property, we introduce dynamic context sizes assignment to each to-be-modified pixel, reducing the pixel numbers in smooth sequence while increasing the pixel numbers in rough sequence to enlarge embedding capacity. Thirdly, we design an opposite direction pairwise embedding scheme to improve the overall embedding performance once again, which is hard to achieve in the original PPVO because of the spatial and causal constraints. As a result, the proposed method achieves significant overall performance compared to state-of-the-art methods.