Investigation of pixel neighbourhood for prediction error-based reversible data hiding using neural networks

Success of a prediction error-based reversible data hiding (RDH) technique depends on a good pixel value predictor. A pixel value predictor predicts a pixel value with the help of its neighbouring pixel values. Considered neighbourhood for pixel value prediction influences the performance of such predictor. Varieties of pixel neighbourhoods have been considered in literature. This paper presents a unique work of its kind to explore the effect of various pixel neighbourhoods. In order to perform this comparative analysis, a neural network is used here to predict a pixel value from a neighbourhood. The best neighbourhood for the pixel value prediction task is determined from the reported experimental observations. The selected neighbourhood is used for pixel value prediction and subsequent RDH scheme. It is observed from the experimental results that the proposed neural network-based adaptive RDH scheme with the selected neighbourhood outperforms majority of the state-of-the-art RDH techniques.