一种多视点视频自动颜色校正系统

针对多视点视频系统中视点间图像颜色不一致的问题,提出了一种多视点视频自动颜色校正系统。通过求取目标图像和源图像间的颜色校正矩阵,判断其是否满足全局校正的要求;对不满足要求的图像,通过图像分割和K-L变换(Karhunen-Loeve transform),建立起目标图像和源图像中各分割区域间的局部映射关系,并通过感兴趣区域匹配,来实现对源图像的校正,最后通过视频跟踪技术实现对视频图像的校正。以标准的多视点测试图像集为例,通过将新方法与直方图匹配、全局一维线性校正算法等进行比较,表明新方法能消除匹配失真的影响,且具有较好的颜色校正效果。研究结果表明该系统可以很好地揭示图像间的颜色变化关系,并且具有很好的内容自适应性,是一种有效的多视点视频图像系统颜色校正方法。     

随机平面弹性问题的协调有限元分析

This paper considers the numerical solution of plane elasticity equations with stochastic Young's modulus and stochastic loads.The stochastic fields are approximated by Karhunen-Loeve expansion and Wiener polynomial chaos expansion along sample paths,and in space continuous Lagrangian finite elements axe used.Error estimates are derived.Numerical experiments are done to verify the theoretical results.     

线性常微分方程参数稳定性的统计推断

对具有随机误差的观测数据, 讨论了常系数线性常微分方程参数稳定性的统计推断问题. 通过残差项的Karhunen-Loeve 分解, 给出了变点检验步骤及其在原假设下的极限分布. 在对立假设下定义了变点的估计, 证明了检验以及估计的一致性. 对常系数二阶常微分方程进行了统计模拟, 结果表明原假设下的极限分布是对真实分布非常好的近似; 对立假设下, 即使输入函数的频率存在0.75% 的变化, 上述检验也能以大概率拒绝原假设. 最后利用上述方法研究了英国中部地区的气温数据, 揭示了数据一些新的特点.     

Data analysis for numerical and categorical individual time-series

Principal components analysis and correspondence analysis may be generalized to handle time-dependent data. For real-valued data the basic tool is the Karhunen-Loeve decomposition. For categorical processes harmonic analysis is presented in terms of reciprocal averaging. Details are given for approximated and interpolated solutions.     

分组Karhun-Loeve变换/整数小波变换高光谱影像准无损压缩新方法

提出了分组Karhunen-Leove变换(KLT)和整数小波变换(IWT)的高光谱图像数据压缩方法,并采用整数小波变换技术和Set Partitioning in Hierarchical Trees(SPIHT)压缩编码,实现了对分组Karhun-Loeve变换后的数据压缩。该压缩编码方法与现有压缩方法相比,既保留了Karhun-Loeve变换压缩性能和整数小波变换高压缩比的特点,也宜于实时传输。实验结果表明,分组Karhun-Loeve变换/整数小波变换/SPIHT在相同压缩比下,峰值信噪比比Karhun-Loeve变换/小波变换/WSFCVQ、Karhun-Loeve变换/小波变换/改进的对块零树编码压缩和Karhun-Loeve变换/WT/FSVQ分别提高了6 dB,9 dB和8 dB,运算时间减少一半,整体压缩性能有了较大的提高。     

Inter-channel de-correlation for perceptual audio coding

Sound reproduction is evolving towards multi-channel systems with a growing number of channels. Consequently, high quality multi-channel codecs are required. Last generation perceptual audio codecs, represented by MPEG advanced audio coder (AAC), can efficiently code typical surround multi-channel material but may benefit from a previous block of inter-channel de-correlation, for certain audio recordings. These recordings present high correlation between non-symmetric channels, or correspond to loudspeaker arrangements different from surround, such as linear loudspeaker arrays. In order to valuate the advantages of this new coding approach, a multi-channel perceptual quality measure is developed.     

The robustness of an efficient probabilistic data-based tool for simulating the non-stationary response of non-linear systems

The stochastic response of dynamic systems has been an area of considerable interest for some time in the analysis of risk and structural reliability. The authors, in previous work, have developed a method which can analyze the response of linear multi-degree-of-freedom systems to completely general data-based non-stationary excitations in a highly efficient and analytical form. The authors extended this work to non-linear system response by using equivalent linearization techniques. This paper explores the range of application of the extension to the analysis of non-linear systems through the use of real and simulated data-sets. In particular, sensitivity issues of non-Gaussianity of the excitation data, and the degree of response non-linearity of the dynamic system, are investigated for their effect on the estimated response using this equivalent linearization-based approach.     

Karhunen-Loeve expansions for the m-th order detrended Brownian motion

The m-th order detrended Brownian motion is defined as the orthogonal component of projection of the standard Brownian motion onto the subspace spanned by polynomials of degree up to m. We obtain the Karhunen-Loeve expansion for the process and establish a connection with the generalized (m-th order) Brownian bridge developed by MacNeill (1978) in the study of distributions of polynomial regression. The resulting distribution identity is also verified by a stochastic Fubini approach. As applications, large and small deviation asymptotic behaviors for the L ₂ norm are given.     

受大气湍流影响的光学波前模拟方法研究

介绍了模拟自适应光学系统中受大气湍流影响的光学波前的四种方法，即基于Zernike多项式的K—L函数展开法、小波法、Fourier法以及ARMA法。分析比较了四种方法模拟精度和速度。结果表明，前两种方法不论是精度还是速度上都比较好，更适合湍流波前的模拟。     

A method for solving stochastic eigenvalue problems

We present a novel approach for calculating stochastic eigenvalues of differential and integral equations as well as for random matrices. Five examples based on very different types of problem have been analysed and detailed numerical results obtained. It would seem that the method has considerable promise. The essence of the method is to replace the stochastic eigenvalue problem λ(ξ)?(ξ)=A(ξ)?(ξ), where ξ is a set of random variables, by the introduction of an auxiliary equation in which . This changes the problem from an eigenvalue one to an initial value problem in the new pseudo-time variable t. The new linear time-dependent equation may then be solved by a polynomial chaos expansion (PCE) and the stochastic eigenvalue and its moments recovered by a limiting process. This technique has the advantage of avoiding the non-linear terms in the conventional method of stochastic eigenvalue calculation by PCE, but it does introduce an additional, ‘pseudo-time’, independent variable t. The paper illustrates the viability of this approach by application to several examples based on realistic problems.