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Multimedia Tools and Applications

, Volume 77, Issue 7, pp 8805–8821 | Cite as

Reversible data hiding scheme using sub-sampled image exploiting Lagrange’s interpolating polynomial

  • Biswapati Jana
Article

Abstract

In this paper, a new reversible data hiding scheme has been proposed using lagrange’s interpolating polynomial on interpolated sub-sampled images. First, we generate sub-sampled images from original image and enlarge its size using image interpolation. Now, we convert secret message using lagrange interpolating polynomial and generate new secret message. The new secret message is divided and stored within interleaved pixel of each interpolated sub-sampled images. At the receiver end, new secret message is extracted from interleaved pixel of each sub-sampled stego images and then lagrange’s interpolation is applied to generate original secret message. The security has been enhanced due to the distributive nature of hidden data within multiple images. The original pixels are not effected during data embedding which assure reversibility. The proposed scheme provides average embedding capacity with good visual quality measured by peak signal to noise ratio (PSNR) which is greater than 50 dB. It is observed that the proposed scheme provides better performance than other existing data hiding schemes in terms of data embedding capacity, visual quality and security. We have analyzed our stego images through RS analysis, calculate relative entropy, standard deviation and correlation coefficient of original and stego image to show the robustness under various steganographic attacks.

Keywords

Steganography Sub-sampled image Reversible data hiding Lagrange interpolation Image interpolation RS analysis Relative entropy 

Notes

Acknowledgements

The author is grateful to the anonymous reviewers for their invaluable comments and recommendations to improve our paper. This work is supported by UGC Innovative project grant under Vidyasagar University (Grant Nos: VU/Innovative/ Sc/06/2015, Dated: 17.06.2015).

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Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  1. 1.Department of Computer ScienceVidyasagar UniversityMidnaporeIndia

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