Adaptive error prediction method based on multiple linear regression for reversible data hiding

Abstract

To improve the prediction accuracy, this paper proposes an adaptive error prediction method based on multiple linear regression (MLR) algorithm. The MLR matrix function that indicates the inner correlations between the pixels and their neighbors is established adaptively according to the consistency of pixels in local area of a natural image, and thus the objected pixel is predicted accurately with the achieved MLR function that denotes the consistency of the neighboring pixels. Compared with the conventional methods that predict the objected pixel with fixed predictors through simple arithmetic combination of its surroundings pixel, the proposed method can provide a comparatively spare prediction-error image for data embedding, and thus can improve the performance of reversible data hiding. Experimental results show that the proposed method outperforms most state-of-the-art error prediction algorithms.