A Multiple Linear Regression Based High-Performance Error Prediction Method for Reversible Data Hiding

Document Type

Conference Proceeding

Publication Date

1-1-2018

Abstract

In this paper, a high-performance error-prediction method based on Multiple Linear Regression (MLR) algorithm is first proposed to improve the performance of Reversible Data Hiding (RDH). The MLR matrix function that indicates the inner correlations between the pixels and its neighbors is established adaptively according to the consistency of pixels in local area of a natural image, and thus the object pixel is predicted accurately with the achieved MLR function that satisfies the consistency of the neighboring pixels. Compared with conventional methods that only predict the object pixel with fixed parameters predictors through simple arithmetic combination of its surroundings pixel, experimental results show that the proposed method can provide a sparser prediction-error image for data embedding, and thus improves the performance of RDH more effectively than those state-of-the-art error prediction algorithms.

Identifier

85053930413 (Scopus)

ISBN

[9783030000141]

Publication Title

Lecture Notes in Computer Science Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics

External Full Text Location

https://doi.org/10.1007/978-3-030-00015-8_12

e-ISSN

16113349

ISSN

03029743

First Page

135

Last Page

146

Volume

11066 LNCS

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