Quantization-Based Robust Image Watermarking Using the Dual Tree Complex Wavelet Transform

Conventional quantization index modulation (QIM) watermarking uses the fixed quantization step size for the host signal.This scheme is not robust against geometric distortions and may lead to poor fidelity in some areas of content.Thus,we proposed a quantization-based image watermarking in the dual tree complex wavelet domain.We took advantages of the dual tree complex wavelets (perfect reconstruction,approximate shift invariance,and directional selectivity).For the case of watermark detecting,the probability of false alarm and probability of false negative were exploited and verified by simulation.Experimental results demonstrate that the proposed method is robust against JPEG compression,additive white Gaussian noise (AWGN),and some kinds of geometric attacks such as scaling,rotation,etc.

Seismic signal analysis based on the dual-tree complex wavelet packet transform

We tried to apply the dual-tree complex wavelet packet transform in seismic signal analysis. The complex wavelet packet transform (CWPT) combine the merits of real wavelet packet transform with that of complex continuous wavelet transform (CCWT). It can not only pick up the phase information of signal, but also produce better ″focal- izing″ function if it matches the phase spectrum of signals analyzed. We here described the dual-tree CWPT algo- rithm, and gave the examples of simulation and actual seismic signals analysis. As shown by our results, the dual-tree CWPT is a very effective method in analyzing seismic signals with non-linear phase.

Defects Recognition of 3D Braided Composite Based on Dual-Tree Complex Wavelet Packet Transform

Textile-reinforced composites,due to their excellent highstrength-to-low-mass ratio, provide promising alternatives to conventional structural materials in many high-tech sectors. 3D braided composites are a kind of advanced composites reinforced with 3D braided fabrics; the complex nature of 3D braided composites makes the evaluation of the quality of the product very difficult. In this investigation,a defect recognition platform for 3D braided composites evaluation was constructed based on dual-tree complex wavelet packet transform( DT-CWPT) and backpropagation( BP) neural networks. The defects in 3D braided composite materials were probed and detected by an ultrasonic sensing system. DT-CWPT method was used to analyze the ultrasonic scanning pulse signals,and the feature vectors of these signals were extracted into the BP neural networks as samples. The type of defects was identified and recognized with the characteristic ultrasonic wave spectra. The position of defects for the test samples can be determined at the same time. This method would have great potential to evaluate the quality of 3D braided composites.

A New Construction Method for the Dual Tree Complex Wavelet Based on Direction Sensitivity

The conception of 'main direction' of multi-dimensional wavelet is established in this paper, and the capabilities of several classical complex wavelets for representing directional singularities are investigated based on their main directions. It is proved to be impossible to represent directional singularities optimally by a multi-resolution analysis (MRA) of L2(R2). Based on the above results, a new algorithm to construct Q-shift dual tree complex wavelet is proposed. By optimizing the main direction of parameterized wavelet filters, the difficulty in choosing stop-band frequency is overcome and the performances of the designed wavelet are improved too. Furthermore, results of image enhancement by various multi-scale methods are given, which show that the new designed Q-shift complex wavelet do offer significant improvement over the conventionally used wavelets. Direction sensitivity is an important index to the performance of 2D wavelets.

A Dual Tree Complex Discrete Cosine Harmonic Wavelet Transform (ADCHWT) and Its Application to Signal/Image Denoising

A new simple and efficient dual tree analytic wavelet transform based on Discrete Cosine Harmonic Wavelet Transform DCHWT (ADCHWT) has been proposed and is applied for signal and image denoising. The analytic DCHWT has been realized by applying DCHWT to the original signal and its Hilbert transform. The shift invariance and the envelope extraction properties of the ADCHWT have been found to be very effective in denoising speech and image signals, compared to that of DCHWT.

Insect recognition based on integrated region matching and dual tree complex wavelet transform

To provide pest technicians with a convenient way to recognize insects,a novel method is proposed to classify insect images by integrated region matching (IRM) and dual tree complex wavelet transform (DTCWT).The wing image of the lepidopteran insect is preprocessed to obtain the region of interest (ROI) whose position is then calibrated.The ROI is first segmented with the k-means algorithm into regions according to the color features,properties of all the segmented regions being used as a coarse level feature.The color image is then converted to a grayscale image,where DTCWT features are extracted as a fine level feature.The IRM scheme is undertaken to find K nearest neighbors (KNNs),out of which the nearest neighbor is searched by computing the Canberra distance of DTCWT features.The method was tested with a database including 100 lepidopteran insect species from 18 families and the recognition accuracy was 84.47%.For the forewing subset,a recognition accuracy of 92.38% was achieved.The results showed that the proposed method can effectively solve the problem of automatic species identification of lepidopteran specimens.

Image inpainting using complex 2-D dual-tree wavelet transform

The dual-tree complex wavelet transform is a useful tool in signal and image process- ing. In this paper, we propose a dual-tree complex wavelet transform （CWT） based algorithm for image inpalnting problem. Our approach is based on Cai, Chan, Shen and Shen＇s framelet-based algorithm. The complex wavelet transform outperforms the standard real wavelet transform in the sense of shift-invariance, directionality and anti-aliasing. Numerical results illustrate the good performance of our algorithm.

Study on Curative Effect of Perforated Injection of Zinc-ammonia Complex on Rosette Disease of Fruit Tree

[ Objective ] The paper was to explore a kind of zinc preparation suitable for injection on trees with fast, efficient and safe cure effect on physiological disease of zinc deficiency. [Method] Taking three years old apple, pear, peach and grape trees as the materials, the author studied the absorption condition of these trees to six kinds of zinc substances and their security. The sealed curative effects of the injected zinc substances which were harmful and could be absorbed steadily by the fruit trees against rosette disease were studied. [ Result] The results of absorption condition and security experiments showed that only zinc-mmnonia complex could be absorbed steadily and safely throughout four seasons. When apple, pear, peach and grape trees affected by rosette disease were injected with zinc- ammonia complex, the leaves of those trees started to grow obviously after 10 d; the internodes of diseased branches elongated, the leaves turned bigger, and the ap- pearance of branches became normal after about 25 d. [ Conclusion] The curative effect of perforated injection of zinc-ammonia complex on fruit tree rosette disease was remarkable. The results also provided a new way for the cure of deficiency diseases of other trace elements.

Decision Tree Complexity of Graph Propertieswith Dimension at Most5

A graph property is a set of graphs such that if the set contains some graph G then it also contains each isomorphic copy of G (with the same vertex set). A graph property P on n ventices is said to be elusive, if every decision tree algorithm recognizing P must examine all n(n - 1)/2 pairs of ventices in the worst case. Karp conjectured that every nontrivial monotone graph property is elusive. In this paper, this conjecture is proved for some cases. Especially,it is shown that if the abstract simplicial complex of a nontrivial monotone graph property P has dimension not exceeding 5, then P is elusive.

Complex tree: the basic framework of protein-protein interaction networks

In living cells, proteins are dynamically connec ted through biochemical reactions, so its functi onal features are properly encoded into protein protein interaction networks (PINs). Up to pres ent, many efforts have been devoted to exploring the basic feature of PINs. However, it is still a challenging problem to explore a universal pr operty of PINs. Here we employed the complex networks theory to analyze the proteinprotein interactions from Database of Interacting Prot ein. Complex tree: the unique framework of PINs was revealed by three topological properties of the giant component of PINs (GCOP), including rightskewed degree distributions, relatively sm all clustering coefficients and short characteristic path lengths. Furthermore, we proposed a no nlinearly growth model: complex tree model to reflect the tree framework, the simulation resu lts of this model showed that GCOPs were well represented by our model, which could be help ful for understanding the treestructure: basic framework of PINs. Source code and binaries freely available for download at http://cic.scu. edu.cn/bioinformatics/STM/STM_code.rar.

Automatic Sleep Spindle Detection with EEG Based on Complex Demodulation Method and Decision Tree Model

Sleep spindle is the characteristic waveform of electroencephalogram (EEG) which is important for clinical diagnosis. In this study, an automatic sleep spindle detection method was developed. The EEG signals were recorded based on the standard polysomnogram (PSG) measurement. A preprocessing procedure is introduced to exclude the unnecessary data segments and normalized the necessary data segments. Complex demodulation method is adopted to detect the candidate sleep spindle waveforms and calculate the features. The sleep spindles are recognized based on a decision tree model. Finally, the detected sleep spindles were utilized to amend the sleep stage recognition results. The sleep EEG data from 3 patients with sleep disorders were analyzed. The obtained results showed that the detected sleep spindles in EEG signal improved the accuracy of sleep stage recognition.

NEW METHOD OF EXTRACTING WEAK FAILURE INFORMATION IN GEARBOX BY COMPLEX WAVELET DENOISING

Because the extract of the weak failure information is always the difficulty and focus of fault detection. Aiming for specific statistical properties of complex wavelet coefficients of gearbox vibration signals, a new signal-denoising method which uses local adaptive algorithm based on dual-tree complex wavelet transform （DT-CWT） is introduced to extract weak failure information in gear, especially to extract impulse components. By taking into account the non-Gaussian probability distribution and the statistical dependencies among wavelet coefficients of some signals, and by taking the advantage of near shift-invariance of DT-CWT, the higher signal-to-noise ratio （SNR） than common wavelet denoising methods can be obtained. Experiments of extracting periodic impulses in gearbox vibration signals indicate that the method can extract incipient fault feature and hidden information from heavy noise, and it has an excellent effect on identifying weak feature signals in gearbox vibration signals.

计算 3-Tree 网络全终端可靠度的线性时间算法

对于一般网络，计算全终端可靠度是ＮＰ难问题．３Ｔｒｅｅ网络是一类具有特殊结构和性质的网络．利用三角子图到Ｋ４的化简，给出了一个计算３Ｔｒｅｅ网络全终端可靠度的线性时间算法．

Exploration into characters＇ psychological complex in The woodlanders

This essay focuses on three main characters in Thomas Hardy＇s The woodlanders, and analyzes their psychological complex： John South--Tree Complex, Giles Winterborne--Inferiority Complex, and Marty South---Survival of the Fittest, showing the relationship between man and nature.

Recognition of Group Activities Using Complex Wavelet Domain Based Cayley-Klein Metric Learning

A group activity recognition algorithm is proposed to improve the recognition accuracy in video surveillance by using complex wavelet domain based Cayley-Klein metric learning.Non-sampled dual-tree complex wavelet packet transform(NS-DTCWPT)is used to decompose the human images in videos into multi-scale and multi-resolution.An improved local binary pattern(ILBP)and an inner-distance shape context(IDSC)combined with bag-of-words model is adopted to extract the decomposed high and low frequency coefficient features.The extracted coefficient features of the training samples are used to optimize Cayley-Klein metric matrix by solving a nonlinear optimization problem.The group activities in videos are recognized by using the method of feature extraction and Cayley-Klein metric learning.Experimental results on behave video set,group activity video set,and self-built video set show that the proposed algorithm has higher recognition accuracy than the existing algorithms.

PMTree:一种高效的事件流模式匹配方法

复杂事件处理技术从多个持续事件流中分析并提取满足特定模式的事件序列.高吞吐率场景下,如何快速准确地识别事件序列是复杂事件处理技术中一个非常重要的问题.现在事件流的模式匹配方法——NFA、Petri网、有向图等——存在语义描述能力不足、部分算子实现代价高等缺陷.针对这一现状,设计并实现了一种基于树的模式匹配方法——PMTree.PMTree定义了事件模型及相应事件算子,将事件序列映射为树节点,同时将时间窗口约束及谓词约束等放置在相应节点,这些树节点连接成一棵PMTree来支持实时的事件筛选与过滤.进一步研究了PMTree构建过程中的优化策略,并提出了开销模型以及优化构建算法,以尽可能减少模式匹配开销.实验结果表明,相同测试条件下基于PMTree实现的复杂事件处理引擎Cesar吞吐率是基于NFA实现的开源引擎Esper的3～6倍,并且在不同事件量或事件序列复杂度下性能表现稳定.

Tracking of Non-Rigid Object in Complex Wavelet Domain

In this paper we have proposed an object tracking method using Dual Tree Complex Wavelet Transform (DTCxWT). The proposed method is capable of tracking the moving object in video sequences. The object is assumed to be deform-able under limit i.e. it may change its shape from one frame to another. The basic idea in the proposed method is to decompose the image into two components: a two dimensional motion and a two dimensional shape change. The motion component is factored out while the shape is explicitly represented by storing a sequence of two dimensional models. Each model corresponds to each image frame. The proposed method performs well when the change in the shape in the consecutive frames is small however the 2-D motion in consecutive frames may be large. The proposed algorithm is capable of handling the partial as well as full occlusion of the object.

二叉树CreateBTree算法的改进

在分析二叉树的 Create BTree算法的基础上 ,利用线性探测再散列方法对 Create B-Tree算法的中序遍历序列进行预处理来改进 Create BTree算法 ,使得改进后的 Create BTree算法在最差情况下 ,时间复杂度由 O(N 2 )降为 O(N )。

Complexity Analysis of Mixed Constraint Satisfaction Problems

This paper analyzes the resolution complexity of a random CSP model named model RBmix, the instance of which is composed by constraints with different length. For model RBmix, the existence of phase transitions has been established and the threshold points have been located exactly. By encoding the random instances into CNF formulas, it is proved that almost all instances of model RBmix have no tree-like resolution proofs of less than exponential size. Thus the model RBmix can generate abundant hard instances in the threshold. This result is of great significance for algorithm testing and complexity analysis in NP-complete problems.

基于视觉传达技术的激光光斑图像超分辨率重建方法

激光光斑图像在成像过程中易受到成像条件和成像方式的限制,导致激光光斑图像的分辨率比较低,难以满足实际需求。为此,提出基于视觉传达技术的激光光斑图像超分辨率重建方法。采用视觉传达技术采集激光光斑图像,并使用双树复小波阈值方法对激光光斑图像去噪处理,通过改进稠密神经网络提取激光光斑图像特征,基于奇异值分解方法降低字典中原子的数目,改进稀疏表达正则化方法,实现激光光斑图像的超分辨率重建。实验结果表明,所提方法的低分辨率图像重建结果与原始图像更加接近,重建图像的结构相似度均在0.9以上,证明该方法的重建效果好、更适合实际应用。