Abstract
This article reports on a lossless data hiding scheme for digital images where the data hiding capacity is either determined by minimum acceptable subjective quality or by the demanded capacity. In the proposed method data is hidden within the image prediction errors, where the most well-known prediction algorithms such as the median edge detector (MED), gradient adjacent prediction (GAP) and Jiang prediction are tested for this purpose. In this method, first the histogram of the prediction errors of images are computed and then based on the required capacity or desired image quality, the prediction error values of frequencies larger than this capacity are shifted. The empty space created by such a shift is used for embedding the data. Experimental results show distinct superiority of the image prediction error histogram over the conventional image histogram itself, due to much narrower spectrum of the former over the latter. We have also devised an adaptive method for hiding data, where subjective quality is traded for data hiding capacity. Here the positive and negative error values are chosen such that the sum of their frequencies on the histogram is just above the given capacity or above a certain quality.
Similar content being viewed by others
References
Alattar AM (2004) Reversible watermark using the difference expansion of a generalized integer transform. IEEE Trans Image Process 13(8):1147–1156
Celik MU, Sharma G, Tekalp AM, Saber E (2005) Lossless generalized-LSB data embedding. IEEE Trans Image Process 14(2):253–266
Chang CC, Lin CY (2006) Reversible steganography for VQ-compressed images using side matching and relocation. IEEE Trans Inf Forensics Security 1(4):493–501
Chang CC, Tai WL, Lin CC (2006) A reversible data hiding scheme based on side match vector quantization. IEEE Trans Circuits Syst Video Techn 16(10):1301–1308
Fallahpour M, Sedaaghi MH (2007) High capacity lossless data hiding based on histogram modification. IEICE Tran Electron Express 4(7):205–210
Feng JB, Lin IC, Tsai CS, Chu YP (2006) Reversible watermarking: current status and key issues. Int J Netw Secur 2(3):161–171
Fridrich J, Goljan M, Du R (2001) “Invertible authentication”, in: Proceedings of SPIE Photonics West, vol. 3971, Security and Watermarking of Multimedia Contents III, San Jose, CA, pp. 197–208
Gao X, An L, Li X, Tao D (2009) Reversibility improved lossless data hiding. Signal Processing 89(10):2053–2065
Hong W, Chen TS, Shiu CW (2008) Reversible data hiding based on histogram shifting of prediction errors. Proceedings of the International Symposium on Intelligent Information Technology Application Workshop 00 292–295
Hwang JH, Kim JW, CHoi JU (2006) A reversible watermarking based on histogram shifting. LNCS 4283:348–361
Jiang J, Guo B, Yang SY (2000) Revisiting the JPEG-LS prediction scheme. IEE Proc—Vision, Image Signal Process 147(6):575–580
Kamstra L, Heijmans JAM (2005) Reversible data embedding into images using wavelet techniques and sorting. IEEE Trans Image Process 14(12):2082–2090
Kim HJ, Sachnev V, Shi YQ, Nam J, Choo HG (2008) A novel difference expansion transform for reversible data embedding. IEEE Trans Information Forensics and Security 3(3):456–465
Kim KS, Lee MJ, Lee HK, Suh YH (2008) Histogram-based reversible data hiding technique using subsampling. Proceedings of the 10th ACM Workshop on Multimedia and Security, pp. 69–74
Lin CC, Hsueh NL (2007) Hiding data reversibly in an image via increasing differences between two neighboring pixels. IEICE Trans Inf & Syst E90–D(12):2053–2059
Ni Z, Shi YQ, Ansari N, Su W (2006) Reversible data hiding. IEEE Trans Circuits Syst Video Technol 16(3):354–362
Shi YQ, Ni Z, Zou D, Liang C, Xuan G (2004) Lossless data hiding: fundamentals, algorithms and applications. in Proc IEEE Int Symp Circuits Syst, Vancouver, BC, Canada, II 33–36
Tian J (2003) Reversible data embedding using a difference expansion. IEEE Trans Circuits Syst Video Technol 13(8):890–896
Tsai PY, Hu YC, Yeh HL (2009) Reversible image hiding scheme using predictive coding and histogram shifting. Signal Processing 89(6):1129–1143
UWaterloo Image Database: http://links.uwaterloo.ca/greyset2.base.html
Weinberger MJ, Seroussi G (2000) The LOCO-I lossless image compression algorithm: principles and standardization into JPEG-LS. IEEE Trans Image Process 9(8):1309–1324
Wu X, Memon N (1997) Context-based, adaptive, lossless image coding. IEEE Trans Commun 45(4):437–444
Xuan G, Shi YQ, Yang C, Zheng Y, Zou D, Chai P (2005) Lossless data hiding using integer wavelet transform and threshold embedding technique. IEEE Int Conf Multimed & Expo (ICME05), Amsterdam, Netherlands, July 6–8
Xuan G, Shi YQ, Chai P, Cui X, Ni Z, Tong X (2007) Optimum histogram pair based image lossless data embedding. Proc. International Workshop on DigitalWatermarking (IWDW07), Guangzhou, China
Acknowledgments
This work is partially supported by the Spanish Ministry of Science and Innovation and the FEDER funds under the grants TSI2007-65406-C03-03 E-AEGIS and CONSOLIDER-INGENIO 2010 CSD2007-00004 ARES.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Fallahpour, M., Megias, D. & Ghanbari, M. Subjectively adapted high capacity lossless image data hiding based on prediction errors. Multimed Tools Appl 52, 513–527 (2011). https://doi.org/10.1007/s11042-010-0486-2
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11042-010-0486-2