1 A HIGH-CAPACITY STEGANOGRAPHY SCHEME FOR JPEG2000 BASELINE SYSTEM Liang Zhang, Haili Wang, and Renbiao Wu, Senior Member, IEEE 1 IEEE TRANSACTIONS ON IMAGE PROCESSING, VOL. 18, NO. 8, AUGUST 2009 Received September 09, 2008; revised April 01, First published April 24, 2009; current version published July 10, Adviser: Chih-Hung Lin Speaker:Po-Kai Shen Date : 98/11/24

22 Outline 1.Author 2.Introduction 3.Jpeg2000 baseline coding system 4.Steganography based on twice bit-plane encoding 5.Redundancy evaluation 6.Synchronization information and scrambling measure 7.Simulation 8.Conclusion

33 Author(1)  Liang Zhang was born in He received the Ph.D. degree in electronic information engineering from Tianjin University, Tianjin, China, in  He is an Associate Professor. He is currently with the Tianjin Key Lab of Advanced Signal Processing in Civil Aviation University of China.  His current research interests include image processing, information hiding, and intelligent visual surveillance.

44 Author(2)  Haili Wang was born in  She is now a postgraduate specializing in signal processing.  Her current research interests include image processing and information hiding.

55 Author(3)  Renbiao Wu (M’95–SM’01) received the B.Sc. And M.Sc. degrees from Northwestern Polytechnic University, Xian, China, in 1988 and 1991, respectively, and the Ph.D. degree from Xidian University, Xian,in 1994, all in electrical engineering.  From May 1994 to February 1996, he was a Postdoctoral Fellow at the College of Marine Engineering, Northwestern Polytechnic University, where he was promoted to Associate Professor in December  From March 1996 to February 1997, he was a Visiting Scholar at the Center for Transportation Research, Virginia Polytechnic Institute and State University,Blacksburg.

66  From March 1997 to December 1998, he was a Visiting Scholar at the Department of Electrical and Computer Engineering, University of Florida,Gainesville.  Since January 1999, he has been with the Tianjin Key Lab for Advanced Signal Processing, Civil Aviation University of China, Tianjin, China, where he is currently a Chaired Professor and director of the lab. Author(3)

77  From August 2004 to January 2005, he was a Distinguished Research Scholar in the Department of Electrical and Electronic Engineering, Imperial College London, London, U.K. Dr. Wu was the recipient of the National Outstanding Young Investigator Award of China in  His research interests include space-time adaptive processing, adaptive arrays, feature extraction and image formation, spectral estimation and their applications to radar and wireless communication systems. Author(3)

88 Introduction 1)Modern information hiding technology is an important branch of information security. 2)Steganography three competing aspects : Capacity ‚Security ƒRobustness

99 Introduction 3)Section III shows procedures of JPEG2000 baseline system and points out the problem due to bitstream truncation. 4)Section IV describes the principle of twice bit-plane encoding and illustrates the operation procedures. 5)Section V gives a detailed description on redundancy evaluation, and explains how embedding points and their intensity are adjusted.

10 Introduction 6)Section VI, we define measures for synchronization and security. 7)Section VII shows the simulation results. 8)Section VIII draws a conclusion.

11 Jpeg2000 baseline coding system  JPEG2000 uses uniform scalar quantizers with enlarged “deadzones.”  Truncating the embedded bitstream associated with any given codeblock has the effect of quantizing the wavelet coefficients in that codeblock more coarsely.  That is to say, there still exists a lossy procedure after entropy encoding.

12 Steganography based on twice bit-plane encoding

13 Steganography based on twice bit-plane encoding 1)There are three sub-steps involved in the determination of embedding points and embedding intensity for a code block. 2)Scrambled synchronization information and secret messages are embedded into the selected embedding points from the lowest embed-allowed bit-plane to higher ones. 3)Secondary bit-plane encoding is operated after information embedding.

14 Steganography based on twice bit-plane encoding  Ensured at the cost of increased computational complexity and slightly changed compression ratio.

15 Redundancy evaluation  Where is the quantized wavelet coefficient with the bits lowerthan the highest no-zero bit are replaced by zeros.  The parameter is the quantization step of the wavelet coefficient. The parameter assumes a value between 0 and 1. According to, a typical value of is 0.7. The result of the first step is denoted as (1)

16 Redundancy evaluation  In the second step, the neighborhood masking effect is exploited to process the wavelet coefficients as the following:(2)  The neighborhood contains wavelet coefficients within a window of N by N, centered at the current position.  The parameter is the total number of wavelet coefficients in the neighborhood. (2)

17 Redundancy evaluation  The parameter assumes a value between 0 and 1, together with, is used to control the strength of embedding intensity adjustment due to neighborhood masking.  The symbol denotes the neighboring wavelet coefficients greater than or equal to 16, and all its bits lower than the highest no-zero bit are set to be zeros. (2)

18 Redundancy evaluation (3) (4)  In the third step, a weighting factor about brightness sensitivity is used in the processing.  The symbol denotes the subband at resolution level.and with orientation.  The symbol denotes the wavelet coefficient located at in subband.  The levels of discrete wavelet decomposition is k.

19 Redundancy evaluation  The pixel value has a dynamic range of [ -128, 127]. The local average brightness is normalized by dividing 128. Then the result of the third step,, is given by (5)  Quantization redundancy is calculated by the following equation: (6)  The redundancy of the wavelet coefficient can be measured by.

20 Redundancy evaluation  Use the wavelet coefficients with not less than 2 to carry message bits.  The rule of adjustment on embedding points and intensity is as follows: 1)If, then this candidate embedding point should be removed. 2)If, then the embedding capacity of this point is determined to be n bits.

21 Synchronization information and scrambling measure  The first part of the synchronization information is a 2-bit flag that indicates whether a certain code block contains secret message.  The second part of the synchronization information is a 12-bit fragment that indicates the length of the secret message embedded in this code block.

22 Synchronization information and scrambling measure  The third part of the synchronization information is a 12-bit fragment that indicates the length of the secret message embedded in this code block.

23 Synchronization information and scrambling measure  A 64-bit secret key is used as a seed to generate a sequence of pseudo random binary numbers, which is used to scramble the message bits.  N is the total number of message bits.  The symbol denotes the message bit, and the binary number of the pseudo random sequence. The operator ⊕ denotes binary addition. The scrambled message bits, denoted as, are to be embedded into selected wavelet coefficients.

24 Simulation Fig. 6. (a)Original image used as cover media. (b)the binary logo image used as secret message.

25 Simulation  In the first step, the lowest embed-allowed bit-plane of each code block is determined.  In the second step, the wavelet coefficients with magnitudes not less than a given threshold are chosen as candidate embedding points.  In the third step, the candidate embedding points are adjusted image adaptively based on redundancy evaluation to increase hiding capacity  In the fourth step, we embed message bits into the selected wavelet coefficients and finish encoding the stego-image

26 Simulation  The threshold is set to 16  The parameters in those equations are set to be: N=5, α=0.7, β=0.2  Evaluation results for wavelet coefficients A, B, and D are as follows:

27 Simulation 1)If, then this candidate embedding point should be removed. 2)If, then the embedding capacity of this point is determined to be n bits. B: D:

28 Simulation  Experiment shows that information hiding has caused slight change on PSNR (Peak Signal to Noise Ratio) and the actual compression ratio.

29 Simulation  In order to test and measure the effectiveness on hiding capacity enlargement, we simply bypass the redundancy evaluation for comparison. Two methods are tested in the experiments.  Method 1: With redundancy evaluation.  Method 2: Without redundancy evaluation.

30 Simulation Fig. 10. (a) Crown (b) Baboon TABLE I HIDING CAPACITY OF THE THREE TEST IMAGES （ A compression ratio of 0.8 bits per pixel ）

31 Simulation Fig. 11. Hiding capacity of different compression ratios.

32 Simulation Fig. 12. Four images in the database

33 Simulation Fig. 13. ROC curves tested on different payloads.

34 Simulation  The detector does work only if the message length greatly exceeds the hiding capacity.  The proposed steganography scheme can be considered undetectable in the situation of lower payloads than hiding capacity.

35 Conclusion  The contributions of this work are mainly focused on dealing with two problems: bitstream truncation and redundancy measurement.

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