Secure Binary Image Steganography with Distortion Measurement Based on Prediction

Document Type

Article

Publication Date

5-1-2020

Abstract

In this paper, a binary image steganographic scheme is presented, which aims at minimizing the embedding distortions measured by prediction. A prediction model of the center pixel's value is established in a 3 × 3 local region. A concept of 'uncertainty' is introduced to represent the prediction result and the uncertainty is defined as the proximity of probabilities about whether the center pixel is black or white. A pixel with high uncertainty means that it is hard to distinguish whether it has been flipped or not, and thus the distortion introduced by flipping this pixel is small. The uncertainty is an appended statistical explanation of human visual perception and the distortion measurement based on it can evaluate the embedding changes on both vision and statistics. Benefiting from the statistics, uncertainty can evaluate the distortion influence in an extended local region. To play the advantage of distortion measurement, the syndrome-trellis code (STC) is employed to minimize the embedding distortions. Comparisons with prior schemes demonstrate that the proposed steganographic scheme achieves high vision imperceptibility and statistical security.

Identifier

85084727926 (Scopus)

Publication Title

IEEE Transactions on Circuits and Systems for Video Technology

External Full Text Location

https://doi.org/10.1109/TCSVT.2019.2903432

e-ISSN

15582205

ISSN

10518215

First Page

1423

Last Page

1434

Issue

5

Volume

30

Grant

201804020068

Fund Ref

National Natural Science Foundation of China

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