  An accurate predictor is crucial for histogram-shifting (HS) based reversible
data hiding methods. The embedding capacity is increased and the embedding
distortion is decreased simultaneously if the predictor can generate accurate
predictions. In this paper, we propose an accurate linear predictor based on
weighted least squares (WLS) estimation. The robustness of WLS helps the
proposed predictor generate accurate predictions, especially in complex texture
areas of an image, where other predictors usually fail. To further reduce the
embedding distortion, we propose a new embedding method called dynamic
histogram shifting with pixel selection (DHS-PS) that selects not only the
proper histogram bins but also the proper pixel locations to embed the given
data. As a result, the proposed method can obtain very high fidelity marked
images with low bit-rate data embedded. The experimental results show that the
proposed method outperforms the state-of-the-art low bit-rate reversible data
hiding method.
