Computer Science ›› 2022, Vol. 49 ›› Issue (9): 340-346.doi: 10.11896/jsjkx.220300238

• Information Security • Previous Articles     Next Articles

Bi-histogram Shifting Reversible Data Hiding Method After Compressed Differences

HAO Jie, PING Ping, FU De-yin, ZHAO Hong-ze   

  1. School of Computer & Information,Hohai University,Nanjing 211100,China
  • Received:2022-03-25 Revised:2022-06-03 Online:2022-09-15 Published:2022-09-09
  • About author:HAO Jie,born in 1998,postgraduate,is a member of China Computer Federation.Her main research interests include reversible data hiding and so on.
    PING Ping,born in 1982,Ph.D,asso-ciate professor.Her main research in-terests include network and information security.
  • Supported by:
    National Natural Science Foundation of China(61902110).

Abstract: Reversible data hiding(RDH) based on histogram shifting(HS) is the most common technology in current information hiding,especially for the combined method of difference extension and histogram shifting,which can achieve high embedding capacity and low image distortion.In this paper,a reversible information hiding method of bi-histogram shifting after compressed difference is proposed.The algorithm improves the defect of insufficient embedding capacity of the existing method based on histogram shifting by synthesizing three methods of compression,difference and optimized histogram shifting.At the same time,the processing method for the overflow of the image pixel value in the shifting process is also given.At the receiving end,not only can the data be completely extracted,but also lossless image recovery can be performed.After the experiment,a comparison is made with the four current popular schemes.Our method outperforms existing histogram shifting based algorithms in terms of embedding capacity.Compared with other methods,its embedded capacity improves by 23%,11%,57% and 93%.Experimental results show that the proposed method greatly increases the embedding capacity and can effectively realize reversible information hiding with large embedding capacity.

Key words: Compression, Difference, Histogram shifting, Double peak, Reversible data hiding

CLC Number: 

  • TP391
[1]LU W,HE L,YEUNG Y,et al.Secure binary image stegano-graphy based on fused distortion measurement[J].IEEE Transa-ctions on Circuits and Systems for Video Technology,2018,29(6):1608-1618.
[2]WANG Z,QIAN Z,ZHANG X,et al.On improving distortion functions for jpeg steganography[J].IEEE Access,2018(6):74917-74930.
[3]QIN C,JI P,ZHANG X,et al.Fragile image watermarking with pixel-wise recovery based on overlapping embedding strategy[J].Signal Process,2017(138):280-293.
[4]YUAN X C,LI M.Local multi-watermarking method based on robust and adaptive feature extraction[J].Signal Process,2018(149):103-117.
[5]QIAN Z X,ZHOU H,ZHANG W M,et al.Robust steganography using texture synthesis[M]//Advances in Intelligent Information Hiding and Multimedia Signal Processing.Cham:Sprin-ger,20177:25-33.
[6]SHI Y Q,LI X D,ZHANG X P,et al.Reversible data hiding:Advances in the past two decades[J].IEEE Access,2016,4:3210-3237.
[7]LI X L,ZHANG W M,GUI X L,et al.Efficient Reversible Data Hiding Based on Multiple Histograms Modification[J].IEEE Transactions on Information Forensics and Security,2015,10(9):2016-2017.
[8]ZENG X T,LI Z,PING L D.Reversible data hiding schemeusing reference pixel and multilayer embedding[J].AEU-International Journal of Electronics and Communications,2012,66(7):532-539.
[9]ZHANG T C,HOU T S,WENG S W,et al.Adaptive reversible data hiding with contrast enhancement based on multi-histogram modification[J/OL].IEEE Transactions on Circuits and Systems for Video Technology,2022.https://ieeexplore.ieee.org/document/9691384.
[10]BARTON J M.Method and apparatus for embedding authentication information within digital data:US Patent,564997[P].1997-07-08.
[11]WEINBERGER M J,RISSANEN J J,ARPS R B.Applications of universal context modeling to lossless compression of gray-scale images[J].IEEE Transactions on Image Processing,1996,5(4):575-586.
[12]ZHANG W M,HU X C,LI X L,et al.Recursive HistogramModification:Establishing Equivalency Between Reversible Data Hiding and Loss less Data Compression[J].IEEE Transactions on Image Processing,2013,22(7):2775-2785.
[13]TIAN J.Reversible data embedding using a difference expansion[J].IEEE Transactions on Circuits and Systems for Video Technology,2003,13(8):890-896.
[14]OU B,LI X L,WANG J W.High-fidelity reversible data hiding based on pixel value-ordering and pairwise prediction error expansion[J].Journal of Visual Communication and Image Representation,2016(39):12-23.
[15]WANG J X,NI J Q,ZHANG X,et al.Rate and Distortion Optimization for Reversible Data Hiding Using Multiple Histogram Shifting[J].IEEE Transactions on Cybernetics,2017,47(2):315-326.
[16]TANG J R,ISA N A M.Bi-histogram equalization using modified histogram bins[J].Applied Soft Computing,2017(55):31-43.
[17]WANG J X,CHEN X,NI J Q,et al.Multiple Histograms Based Reversible Data Hiding:Framework and Realization[J].IEEE Transactions on Circuits and Systems for Video Technology,2020,30(8):2313-2328.
[18]TIAN J.Reversible watermarking by difference expansion[J/OL].Proceedings of Workshop on Multimedia & Security,2002.https://www.researchgate.net/publication/228809844_Reversible_watermarking_by_difference_expansion.
[19]HSU F H,WU M H,WANG S J.Reversible data hiding using side-match predictions on steganographic images[J].Multimedia Tools and Applications,2013,67(3):571-591.
[20]CHEN Y H,HUANG H C,LIN C C.Block-based reversible data hiding with multi-round estimation and difference alteration[J/OL].Multimedia Tools and Applications,2015:1-26.https://link.springer.com/article/10.1007/s11042-015-2825-9.
[21]TSAI Y Y,TSAI D S,LIU C L.Reversible data hiding scheme based on neighboring pixel differences[J].Digital Signal Process,2013,23(3):919-927.
[22]HU Y,LEE H,LI J.DE-Based Reversible Data Hiding WithImproved Overflow Location Map[J].IEEE Transactions on Circuits and Systems for Video Technology,2009,19(2):250-260.
[23]THODI D M,RODRIGUEZ J J.Expansion Embedding Techniques for Reversible Watermarking[J].IEEE Transactions on Image Processing,2007,16(3):721-730.
[24]NGUYEN T S,CHANG C C,HUYNH N T.A novel reversible data hiding scheme based on difference-histogram modification and optimal EMD algorithm[J].Journal of Visual Communication and Image Representation,2015(33):389-397.
[25]XUE B,LI X,WANG J,et al.Improved reversible data hiding based on two-dimensional difference-histogram modification[J].Multimedia Tools and Applications,2016,76(11):1-19.
[26]ARHAM A,HUGROHO H A,ADJI T B.Multiple layer data hiding scheme based on difference expansion of quad☆[J].Signal Processing,2017(137):52-62.
[27]NI Z C,SHI Y Q,ANASRI N,et al.Reversible data hiding[J].IEEE Transactions on Circuits and Systems for Video Techno-logy,2006,16(3):354-362.
[28]FALLAHPOUR M,SEDAAGHI M H.High capacity losslessdata hiding based on histogram modification[J].IEICE Electron Express,2007,4(7):205-210.
[29]TSAI P,HU Y C,YEH H L.Reversible image hiding schemeusing predictive coding and histogram shifting[J].Signal Proces-sing,2009,89(6):1129-1143.
[30]BISWAS T,HASAN M M,DEBNATH T.A New Method of Reversible Data Hiding Based on Compressed Gray Level Histogram Shifting[C]//2016 3rd International Conference on Electrical Engineering and Information Communication Technology.IEEE,2016:1-6.
[31]JUNG K H.A high-capacity reversible data hiding scheme based on sorting and prediction in digital images[J].Multimedia Tools and Applications,2017,76(11):13127-13137.
[32]JIA Y J,YIN Z X,ZHANG X P,et al.Reversible data hiding based on reducing invalid shifting of pixels in histogram shifting[J].Signal Processing,2019(163):238-246.
[33]PAN Z B,GAO X Y,GAO E,et al.Adaptive Complexity for Pixel-Value-Ordering Based Reversible Data Hiding[J].IEEE Signal Processing Letters,2020(27):912-919.
[1] ZHOU Lian-bing, ZHOU Xiang-zhen, CUI Xue-rong. Compressed Image Encryption Scheme Based on Dual Two Dimensional Chaotic Map [J]. Computer Science, 2022, 49(8): 344-349.
[2] CHU Yu-chun, GONG Hang, Wang Xue-fang, LIU Pei-shun. Study on Knowledge Distillation of Target Detection Algorithm Based on YOLOv4 [J]. Computer Science, 2022, 49(6A): 337-344.
[3] CHENG Xiang-ming, DENG Chun-hua. Compression Algorithm of Face Recognition Model Based on Unlabeled Knowledge Distillation [J]. Computer Science, 2022, 49(6): 245-253.
[4] CHEN Zhuang, ZOU Hai-tao, ZHENG Shang, YU Hua-long, GAO Shang. Diversity Recommendation Algorithm Based on User Coverage and Rating Differences [J]. Computer Science, 2022, 49(5): 159-164.
[5] MA Bin, HOU Jin-cheng, WANG Chun-peng, LI Jian, SHI Yun-qing. High Capacity Reversible Data Hiding Algorithm for Audio Files Based on Code Division Multiplexing [J]. Computer Science, 2021, 48(9): 298-305.
[6] WANG Sheng, ZHANG Yang-sen, CHEN Ruo-yu, XIANG Ga. Text Matching Method Based on Fine-grained Difference Features [J]. Computer Science, 2021, 48(8): 60-65.
[7] CHEN Zhi-wen, WANG Kun, ZHOU Guang-yun, WANG Xu, ZHANG Xiao-dan, ZHU Hu-ming. SAR Image Change Detection Method Based on Capsule Network with Weight Pruning [J]. Computer Science, 2021, 48(7): 190-198.
[8] QIAN Xin-yuan, WU Wen-yuan. Identity-based Encryption Scheme Based on R-SIS/R-LWE [J]. Computer Science, 2021, 48(6): 315-323.
[9] WANG Ying-ying, CHANG Jun, WU Hao, ZHOU Xiang, PENG Yu. Intrusion Detection Method Based on WiFi-CSI [J]. Computer Science, 2021, 48(6): 343-348.
[10] LIU Dong, WANG Ye-fei, LIN Jian-ping, MA Hai-chuan, YANG Run-yu. Advances in End-to-End Optimized Image Compression Technologies [J]. Computer Science, 2021, 48(3): 1-8.
[11] JIANG Chong, ZHANG Zong-zhang, CHEN Zi-xuan, ZHU Jia-cheng, JIANG Jun-peng. Data Efficient Third-person Imitation Learning Method [J]. Computer Science, 2021, 48(2): 238-244.
[12] ZHAN Rui, LEI Yin-jie, CHEN Xun-min, YE Shu-han. Street Scene Change Detection Based on Multiple Difference Features Network [J]. Computer Science, 2021, 48(2): 142-147.
[13] DAN Zhou-yang, LIU Fen-lin, GONG Dao-fu. Smoothing Filter Detection Algorithm Based on Middle and Tail Information of Differential Histogram [J]. Computer Science, 2021, 48(11): 234-241.
[14] SUN Yan-li, YE Jiong-yao. Convolutional Neural Networks Compression Based on Pruning and Quantization [J]. Computer Science, 2020, 47(8): 261-266.
[15] JIANG Wen-bin, FU Zhi, PENG Jing, ZHU Jian. 4Bit-based Gradient Compression Method for Distributed Deep Learning System [J]. Computer Science, 2020, 47(7): 220-226.
Viewed
Full text


Abstract

Cited

  Shared   
  Discussed   
No Suggested Reading articles found!