Exploring Reversible Digital Watermarking in Audio Signals Using Additive Interpolation-error Expansion

Author(s):  
Jose Juan Garcia-Hernandez
Author(s):  
Fuqiang Di ◽  
Minqing Zhang ◽  
Yingnan Zhang ◽  
Jia Liu

A novel reversible data hiding algorithm for encrypted image based on interpolation error expansion is proposed. The proposed method is an improved version of Shiu' s. His work does not make full use of the correlation of the neighbor pixels and some additional side information is needed. The proposed method adopts the interpolation prediction method to fully exploit the pixel correlation and employ the Paillier public key encryption method. The algorithm is reversible. In the proposed method, less side information is demanded. The experiment has verified the feasibility and effectiveness of the proposed method, and the better embedding performance can be obtained, compared with some existing RDHEI-P methods. Specifically, the final embedding capacity can be up to 0.74 bpp (bit per pixel), while the peak signal-to-noise ratio (PSNR) for the marked image Lena is 35 dB. This is significantly higher than Shiu's method which is about 0.5 bpp.


2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Fei Wang ◽  
Zhaoxin Xie ◽  
Zuo Chen

Being reversible, the watermarking information embedded in audio signals can be extracted while the original audio data can achieve lossless recovery. Currently, the few reversible audio watermarking algorithms are confronted with following problems: relatively low SNR (signal-to-noise) of embedded audio; a large amount of auxiliary embedded location information; and the absence of accurate capacity control capability. In this paper, we present a novel reversible audio watermarking scheme based on improved prediction error expansion and histogram shifting. First, we use differential evolution algorithm to optimize prediction coefficients and then apply prediction error expansion to output stego data. Second, in order to reduce location map bits length, we introduced histogram shifting scheme. Meanwhile, the prediction error modification threshold according to a given embedding capacity can be computed by our proposed scheme. Experiments show that this algorithm improves the SNR of embedded audio signals and embedding capacity, drastically reduces location map bits length, and enhances capacity control capability.


2017 ◽  
Vol 6 (55) ◽  
pp. 185
Author(s):  
Maksim Viktorovich Gofman ◽  
Anatoliy Adamovich Kornienko ◽  
Evgenij Timofeevich Mironchikov ◽  
Aleksandr Borisovich Nikitin

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