Histogram-Based Reversible Information Hiding Improved by Prediction with the Variance to Enhance Image Quality

Reversible data hiding based on prediction-based is a good technique that can hide message bits into digital images with low distortion. In this paper, we propose a reversible data hiding method based on interleaving prediction and local complexity for enhancing stego-image quality. The thresholds and local complexity are used to determine which predicted error should join the group of pixel shifting or message concealing. If the local complexity is smaller than thresholds, the predicted error will be taken for message hiding or pixel shifting, otherwise, if the local complexity is larger than thresholds, the predicted error will quit joining the process of data concealing and pixel shifting. Therefore, more pixels will avoid executing the process of pixel shifting, resulting to images with lower distortion. The experimental results show that our image quality is superior to other approaches at the same payload.