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

Document Type

Conference Proceeding

Publication Date

8-13-2019

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.

Identifier

85068127903 (Scopus)

Publication Title

Journal of Real Time Image Processing

External Full Text Location

https://doi.org/10.1007/s11554-019-00891-w

ISSN

18618200

First Page

821

Last Page

834

Issue

4

Volume

16

Grant

61502241

Fund Ref

National Natural Science Foundation of China

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