基于易操纵金字塔的多传感器图像融合

针对目前传统方法在图像未完全配准时融合效果差的问题,提出了一种基于易操纵金字塔的多传感器图像融合方法。首先,对多光谱图像进行易操纵金字塔分解;然后,恰当地合并分解得到子带图像系列来构造融合图像对应的易操纵金字塔,并通过逆变换重构融合后图像。最后利用熵和空间频率对该方法的融合性能进行了评估分析,并与基于拉普拉斯变换和小波变换的图像融合方法进行了比较。实验结果表明,该方法综合性能优于基于拉普拉斯变换和基于小波变换等传统图像融合方法,图像未完全配准情况下也能获得好的融合效果。     

A multiscale edge detection algorithm based on wavelet domain vector hidden Markov tree model

The wavelet analysis is an efficient tool for the detection of image edges. Based on the wavelet analysis, we present an unsupervised learning algorithm to detect image edges in this paper. A wavelet domain vector hidden Markov tree (WD-VHMT) is employed in our algorithm to model the statistical properties of multiscale and multidirectional (subband) wavelet coefficients of an image. With this model, each wavelet coefficient is viewed as an observation of its hidden state and the hidden state indicates if the wavelet coefficient belongs to an edge. The WD-VHMT model can be learned by an expectation-maximization algorithm. After the model is learned, we employ an extended Viterbi algorithm to uncover the hidden state sequences according to the maximum a posterior estimation. The experiment results of the edge detection for several images are provided to evaluate our algorithm.     

Efficient wavelet adaptation for hybrid wavelet-large margin classifiers

Hybrid wavelet-large margin classifiers have recently proven to solve difficult signal classification problems in cases where solely using a large margin classifier like, e.g., the Support Vector Machine may fail. In this paper, we evaluate several criteria rating feature sets obtained from various orthogonal filter banks for the classification by a Support Vector Machine. Appropriate criteria may then be used for adapting the wavelet filter with respect to the subsequent support vector classification. Our results show that criteria which are computationally more efficient than the radius-margin Support Vector Machine error bound are sufficient for our filter adaptation and, hence, feature selection. Further, we propose an adaptive search algorithm that, once the criterion is fixed, efficiently finds the optimal wavelet filter. As an interesting byproduct we prove a theorem which allows the computation of the radius of a set of vectors by a standard Support Vector Machine.     

Fast variational design of multiresolution curves and surfaces with B-spline wavelets

Multiresolution modeling provides a powerful tool for complex shape editing. To achieve a better control of deformations and a more intuitive interface, variational principles have been used in such multiresolution models. However, when handling multiresolution constraints, the existing methods often result in solving large optimization systems. Hence, the computational time may become too excessive to satisfy the requirements for interactive design in CAD. In this paper, we present a fast approach for interactive variational design of multiresolution models. By converting all constraints at different levels to a target level, the optimization problem is formulated and solved at the lower level. Thus, the unknown coefficients of the optimization system are significantly reduced. This improves the efficiency of variational design. Meanwhile, to avoid smoothing out the details of the shape in variational modeling, we optimize the change in the deformation energy instead of the total energy of the deformed shape. Several examples and the experimental results are given to demonstrate the effectiveness and efficiency of this approach.     

Optimal wavelet denoising for phonocardiograms

Phonocardiograms (PCGs), recordings of heart sounds, have many advantages over traditional auscultation in that they may be replayed and analysed for spectral and frequency information. PCG is not a widely used diagnostic tool as it could be. One of the major problems with PCG is noise corruption. Many sources of noise may pollute a PCG including foetal breath sounds if the subject is pregnant, lung and breath sounds, environmental noise and noise from contact between the recording device and the skin. An electronic stethoscope is used to record heart sounds and the problem of extracting noise from the signal is addressed via the use of wavelets and averaging. Using the discrete wavelet transform, the signal is decomposed. Due to the efficient decomposition of heart signals, their wavelet coefficients tend to be much larger than those due to noise. Thus, coefficients below a certain level are regarded as noise and are thresholded out. The signal can then be reconstructed without significant loss of information in the signal content. The questions that this study attempts to answer are which wavelet families, levels of decomposition, and thresholding techniques best remove the noise in a PCG. The use of averaging in combination with wavelet denoising is also addressed. Possible applications of the Hilbert transform to heart sound analysis are discussed.     

基于RSA与小波分析的秘密信息隐藏

利用RSA公钥密码体制和小波分析技术,将加密通信和信息隐藏相结合,提出基于RSA与小波分析的秘密信息隐藏方案;对方案各部分进行了详细介绍,并给出信息隐藏的效果图.     

Metis – An Object-Oriented Toolkit for Constructing Virtual Reality Applications

Virtual reality systems provide realistic look and feel by seamlessly integrating three-dimensional input and output devices. One software architecture approach to constructing such systems is to distribute the application between a computation-intensive simulator back-end and a graphics-intensive viewer front-end which implements user interaction. In this paper we discuss Metis, a toolkit we have been developing based on such a software architecture, which can be used for building interactive immersive virtual reality systems with computationally intensive components. The Metis toolkit defines an application programming interface on the simulator side, which communicates via a network with a standalone viewer program that handles all immersive display and interactivity. Network bandwidth and interaction latency are minimized, by use of a constraint network on the viewer side that declaratively defines much of dynamic and interactive behavior of the application.     

Hermitian B-Splines

This paper proposes to study a spline model, called HB-splines, that is in fact a B-spline representation of Hermite splines, combined with some restriction on the differential values at segment boundaries. Although this model does not appear able to offer something new to the computer graphics community, we think that HB-splines deserve to be considered for themselves because they embed many interesting features. First, they include all the classical properties required in a geometric modeling environment (convex hull, local control, arbitrary orders of parametric or geometric continuity). Second, they have a nice aptitude for direct manipulation (i.e. manipulation without using control points). For this purpose, we propose a new graphic widget, called control sails, that offers the user an intuitive way to specify local properties (position, tangent, curvature) of a curve or a surface. Finally, they provide an elegant formulation of a biorthogonal wavelet family, that permits multiresolution manipulations of the resulting curves or surfaces, in a very efficient way.     

表面粗糙度提取的小波频谱法

提出了表面粗糙度的提取新方法。用小波分析方法确定２维轮廓粗糙度评定基准线和３维表面粗糙度评定基准面,能精确地把表面粗糙度与表面其他成分分离,从而提取表面粗糙度。与传统表面粗糙度提取方法比较,此方法评定精度高,实现方便。     

用于信号逼近的最佳正交子波选择方法

离散子波变换将离散时间信号分解为一系列分辨率下的离散逼近和离散细节。紧支的正交规范子波与完全重建正交镜象滤波器组相对应。本文提出一种用于信号最佳逼近的正交子波选择方法,即选择满足一定条件的滤波器的方法。通过对滤波器参数化,可以将带约束的最优化问题转化为无约束最优化问题,通过对参数在一定范围内的搜索,得到最优解。文中给出了计算机模拟的结果。