Title
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.
Year
DOI
Venue
2019
10.1007/s11554-019-00891-w
Journal of Real-Time Image Processing
Keywords
DocType
Volume
Prediction accuracy, Adaptive, Multiple linear regression (MLR), Reversible data hiding (RDH)
Journal
16
Issue
ISSN
Citations 
4
1861-8200
3
PageRank 
References 
Authors
0.38
0
7
Name
Order
Citations
PageRank
Bin Ma111528.36
Xiaoyu Wang216759.60
Qi Li316830.51
Bin Li416921.46
Jian Li516244.60
Chun-peng Wang69314.43
Yun Q. Shi72918199.53