Evaluation of orthogonal and biorthogonal wavelets for video steganography

ABSTRACT

In recent years, information security over the internet has gained enormous immersion due to a technological escalation in communication via digital media. Nowadays, videos are the most common form of media over the internet, and they have gained the attention of video steganography research community for the security of the communication. This paper implemented video steganography using a widely-known transform technique, discrete wavelet transform (DWT) which consists of different orthogonal and biorthogonal filters used for the decomposition of a frame/image. The aim of this paper is to provide a comparative evaluation for orthogonal and biorthogonal DWT filters with different matrices such as MSE, PSNR. The performance of the different filters has been evaluated both quantitatively and qualitatively to investigate the best among them. Also, the best of orthogonal and biorthogonal filters have been further evaluated with other metrics such as SSIM, BER and histogram analysis. Further, the embedding algorithm has been compared with the existing video steganography techniques. The experimental results illustrate that bior 6.8 (biorthogonal filter) outperforms the other orthogonal and biorthogonal filters in terms of visual distortion.     

A novel biorthogonal wavelet network system for off-angle iris recognition

One important category of non-ideal conditions for iris recognition is off-angle iris images. Practically it is very difficult for images to be captured with no offset. It then becomes necessary to account for off angle information in order to maintain robust performance. A biorthogonal wavelet based iris recognition system, previously designed at our lab, is modified and demonstrated to perform off-angle iris recognition. Biorthogonal wavelet network (BWN) are developed and trained for each class. The non-ideal factors are adjusted by repositioning the BWN. To test, along with the real data, synthetic iris images are generated by using affine and geometric transforms of 0°, 10° and 20^° experimentally collected images. The tests were carried out on the experimentally collected off-angle data and synthetically generated data for angles from 0° to 60^° with a resolution of 5^°. This approach is shown to have less constraints than a transformation based iris recognition approach. Iris images off-angle by up to 42^° for synthetic data and up to 45^° for experimental data are successfully recognized.     

Construction of parametric biorthogonal wavelet filter banks with two parameters for image coding

We had presented a simple technique, which is based on the theory of Diophantine equation, for parametrization of popular biorthogonal wavelet filter banks (BWFBs) having the linear phase and arbitrary multiplicity of vanishing moments (VMs), and constructed a type of parametric BWFBs with one free parameter [15]. Here we generalize this technique to the case of two parameters, and construct a type of parametric BWFBs with two free parameters. The closed-form parameter expressions of the BWFBs are derived, with which any two-parameter family of BWFBs having preassigned VMs can be constructed, and six families, i.e., 9/11, 10/10, 13/11, 10/14, 17/11, and 10/18 families, are considered here. Two parameters provide two degrees of freedom to optimize the resulting BWFBs with respect to other criteria. In particular, in each family, three specific rational-coefficient BWFBs with attractive features are obtained by adjusting the parameters: the first is not only very close to a quadrature mirror filter (QMF) bank, but has optimum coding gain; the second possesses characteristics that are close to the irrational BWFB with maximum VMs by Cohen et al.; and the last which has binary coefficients can realize a multiplication-free discrete wavelet transform. In addition, two BWFBs are systematically verified to exhibit performance competitive to several state-of-the-art BWFBs for image compression, and yet require lower computational costs. This work was supported by the Natural Science Foundation of Jiangsu province, China under Grant 07KJD520005.     

McClellan transformation and the construction of biorthogonal wavelet bases of LR

Bidimensional wavelet bases are constructed by means of McClellan's transformation applied to a pair of one-dimensional biorthogonal wavelet filters. It is shown that under some conditions on the transfer function F(ω₁,ω₂) associated to the McClellan transformation and on the dilation matrix D, it is possible to construct symmetric compactly supported biorthogonal wavelet bases of L²(R²). Finally, the construction method is illustrated by means of numerical examples.     

双正交小波在陀螺信号去噪中的应用

本文在用双正交小波对陀螺信号进行不同尺度分解的基础上,结合传统的信号分析方法,得出小波系数是由噪声产生的,从而提出合适的小波去噪方法。本方法在应用中得到较好的去噪效果。     

17/11双正交小波的优化设计及其对图像压缩性能的分析

许多适合于图像编码的小波,如CDF-9/7,Winger-17/11(W-17/11),Villasenor-6/10和10/18(V-6/10和V-10/18)小波,其滤波器系数是无理数,需要用无限的计算精度实现对应的离散小波变换(DWT).该文给出了一种参数化构造17/11双正交小波组的简便方法:首先把小波合成滤波器表示为用两个自由参数表达的三角多项式,然后把双正交小波的精确重构条件归结为一个线性方程组,最后求解此方程组得到对应的小波分解滤波器,从而得到了17/11双正交小波滤波器的参数表达式.通过调整表达式中的自由参数,可以随意构造具有所需特征的17/11线性相位小波滤波器.作为构造实例,构造出一种新的有理系数17/11双正交小波滤波器,它具有优化的编码增益.实验表明:其压缩性能与W-17/11和V-10/18小波滤波器相当,优于CDF-9/7和V-6/10小波滤波器.     

具有抽样性质的双正交子波的逼近性能及其子波抽样的计算

本文主要讨论在具有抽样性质的双正交子波基下Mallat算法的逼近性能及其子波系数的计算。当尺度较小以及尺度较大时,我们依次得到了Mallat算法逼近误差的渐近公式和比较精确的定量估计。结果表明:在这样的子波基下,直接用均匀抽样点代替子波抽样点而无需进行预先滤波,其逼近速度可以达到K阶,这里K是综合尺度函数的阶。模拟实验也显示出它的优点。     

Time–frequency localized three-band biorthogonal wavelet filter bank using semidefinite relaxation and nonlinear least squares with epileptic seizure EEG signal classification

In this paper, we design time–frequency localized three-band biorthogonal linear phase wavelet filter bank for epileptic seizure electroencephalograph (EEG) signal classification. Time–frequency localized analysis and synthesis low-pass filters (LPF) are designed using convex semidefinite programming (SDP) by transforming a nonconvex problem into a convex SDP using semidefinite relaxation technique. Three-band parameterized lattice biorthogonal linear phase perfect reconstruction filter bank (BOLPPRFB) is chosen and nonlinear least squares algorithm is used to determine its parameters values that generate the designed analysis and synthesis LPF such that the band-pass and high-pass filters are also well localized in time and frequency domain. The designed analysis and synthesis three-band wavelet filter banks are compared with the standard two-band filter banks like Daubechies maximally regular filter banks, Cohen–Daubechies–Feauveau (CDF) biorthogonal filter banks and orthogonal time–frequency localized filter banks. Kruskal–Wallis statistical test is employed to measure the statistical significance of the subband features obtained from the various two and three-band filter banks for epileptic seizure EEG signal classification. The results show that the designed three-band analysis and synthesis filter banks both outperform two-band filter banks in the classification of seizure and seizure-free EEG signals. The designed three-band filter banks and multi-layer perceptron neural network (MLPNN) are further used together to implement a signal classifier that provides classification accuracy better than the recently reported results for epileptic seizure EEG signal classification.     

参数化的Deslauriers-Dubuc插值小波——构造及图像编码性能分析

研究了采用提升构造具有任意偶数阶消失矩, 满足对称性, 且仅用一个自由参数表达的 Deslauriers-Dubuc (D-D)双正交插值小波. 首先,采用多相矩阵理论推导出了此类小波存在的条件; 然后,给出了对应小波滤波器和插值小波变换的构造算法. 采用算法具体构造了分别具有消失矩对(4, 2)、(4, 4)、(6, 2)以及(6, 4) 等4类一参数表达的D-D插值小波; 最后, 以自由参数为自变量, 根据编码增益准则, 优化设计了4种用于图像编码的插值小波, 其滤波器系数全为二进制分数, 可实现非乘法运算的离散小波变换(Discrete wavelet transform, DWT). 系统分析表明, 两种小波的压缩性能超过CDF-9/7小波, 对于纹理图像, PSNR增益达到0.44.dB, 并且计算复杂度可降低17%以上. 实验同时表明, 新小波的重构图像具有更好的主观可视质量.     

三带自适应提升双正交滤波器组

该文研究了利用三带提升方法设计三带自适应双正交的滤波器组,在设计中,用于带编码增益作为设计准则,从任意一个滤波器组(标准正交或双正交)开始,通过有序自适应提升方法来设计三带双正交滤波器组。最后,给出例子说明,当选择一个合适初始滤波器组时,子带码增益可以得到较大提高。