High performance reversible data hiding scheme through multilevel histogram modification in lifting integer wavelet transform
- 170 Downloads
This paper proposes a digital image reversible data hiding method in integer lifting transform domain. Owing to the characteristics of the natural image statistics, the neighbor pixel values are similar mostly and hence their differences are observed to be close or equal to zero. A histogram constructed out of this difference factor is exploited for reversible data embedding. Further, data is embedded at multiple levels in the integer lifting wavelet transform domain and hence the proposed scheme facilitates higher payload capacity and exceptional perceptual quality than the conventional single level histogram based techniques. The additional information involved for restoring the cover image and the secret payload is also less compared to the conventional schemes, as the proposed method employs a single parameter called “Embedding Level” for both hiding as well as extraction. Extensive experimentation with huge database of images, five existing RDH schemes and against seven steganalysers, shows that the proposed RDH scheme outperforms other schemes and proves to be a high performance RDH scheme in terms of all the desirable features of a reversible data hiding system like high payload, imperceptible, robustness, losslessness and minimal side information.
KeywordsReversible data hiding Reversible histogram modification Lifting integer wavelet transform Authentication and security
This paper is based upon work supported by the All India Council for Technical Education - Research Promotion Scheme under Grant No. 20/AICTE/RIFD/RPS(POLICY-II)65/2012-13.
- 1.Abdulrahman H, Chaumont M, Montesinos P, and Magnier B (2016) "Color image Steganalysis based on Steerable Gaussian filters bank," Proceedings of the 4th ACM Workshop on Information Hiding and Multimedia Security - IH&MMSec ‘16, 109–114Google Scholar
- 8.Images were obtained from: http://philip.greenspun.com/
- 15.Liu Q, Chen Z (2014) Improved approaches with calibrated neighboring joint density to Steganalysis and seam-carved forgery detection in JPEG images. ACM Trans Intell Syst Technol 5(4):1–30Google Scholar
- 19.NRCS Photo Gallery Home, http://photogallery.nrcs.usda/ .gov/
- 26.Schaefer G, Stich M (2003) UCID: An uncompressed color image database. Proc SPIE Electronic Imaging, Storage and Retrieval Methods and Applications for Multimedia 5307:472–480Google Scholar
- 28.Tang W, Li H, Luo W, Huang J (2015) Adaptive Steganalysis based on embedding probabilities of pixels. IEEE Transactions on Information Forensics and Security 11(4):734–745Google Scholar
- 29.Thodi DM, and Rodríguez JJ (2004) “Prediction-error based reversible watermarking”, Proceedings of International Conference on Image Processing (ICIP '04), vol. 3, 1549–1552Google Scholar
- 41.Yang B, Schmucker M, Niu X, Busch C, and S. Sun (2004) “Reversible image watermarking by histogram modification for integer DCT coefficients”, Proceedings of the 6th Workshop on Multimedia Signal Processing (MMSP '04), 143–146Google Scholar