一种基于核函数的各向异性扩散图像去噪算法

分析了各向异性扩散去噪模型优缺点,针对PM模型不能有效区分噪声和边缘,提出了一种基于核函数的各向异性扩散去噪模型。在该模型中,把图像中噪声与边缘在低维空间的非线性区分关系转变为高维特征空间的线性关系,利用核函数获得高维空间的扩散函数。实验中分别与PM模型、Cattle模型比较分析,证明基于核函数的扩散模型在去除噪声的同时,更好地保留图像的信息,且峰值信噪比最高,去噪性能最优。     

一种改进的各向异性扩散超声图像去噪算法

针对传统的各向异性扩散算法中扩散系数函数的平滑效果不好,扩散过程中扩散门限K的选取依靠经验确定,扩散过程对图像细节保护不足的问题,提出了一种改进的各向异性扩散算法。介绍了几种当前比较典型的各向异性扩散去噪算法;在典型算法分析的基础上提出了一种基于自适应中值滤波的改进扩散模型;根据扩散系数应满足的3个条件及经典的扩散系数函数,提出了改进的扩散模型中的改进扩散系数函数;提出了一种扩散门限K的自适应选取的方法。通过在改进的扩散模型中使用改进的扩散系数函数并结合扩散门限K的自适应选取,对超声图像进行去噪。实验结果表明,所提算法优于PM模型、Catte模型、王常虹算法等,去噪后图像的FOM值比PM模型高出3.34%,PSNR值比PM模型高出0.250 6。该算法在去除散斑噪声的同时有效保护了图像的细节及边缘,有助于医务人员对患病区域的准确诊断。     

基于QPSO优化算法的余弦调制滤波器组设计

提出了一种新的余弦调制滤波器组设计方法,此方法以原型滤波器的阻带衰减作为目标函数,用改进型量子粒子群算法(QPSO)设计最接近满足重构条件的原型低通滤波器,然后在此基础上通过余弦调制得到分析滤波器组和综合滤波器组.实验仿真结果表明,用此方法设计的余弦调制滤波器组(CMFB)具有良好的阻带衰减特性和精确重构性能,在满足性...     

改进型梯形谐振滤波器的带通滤波器设计

提出了一种改进型的梯形滤波器,串联支路由单端谐振器构成,并联支路由单端对谐振器与电容元件组成.以这种改进型梯形谐振滤波器为基本单元,进行了五级级联,同时并联了一个SAW谐振器,设计出一个带通滤波器.利用等效电路模型,得到了频率响应.与传统方法相比,通带内更加平稳,同时获得了一个陡峭的过渡带,带外抑制达30 dB以上.     

一种改进的图像去噪与增强模型

图像的去噪和增强越来越成为制约后续图像一系列处理的瓶颈,为此提出一种图像去噪与增强的混合模型。该模型在各向异性扩散模型的基础上引入边缘指示函数,达到快速识别边缘的目的;在冲击滤波器的基础上,引入含有时间变量的边缘判定函数,适时控制冲击幅度的大小。而后将上述两个模型结合起来,克服了扩散模型仅依赖梯度信息来控制扩散进程的弊端,也适时地锐化了边缘。实验表明该混合模型不仅可以很好地去除图像的斑点噪声,并且可以达到图像增强效果。     

文摘选辑

(一)声表面波技术112 采用线性程序的SAW滤波器的最佳设计——Ruppel,C.:1983 Ultrason.Symp.Proc.,23—26介绍具有任意通带和群延迟响应的SAW带通滤波器的设计方法.用δ函数模型解释了滤波器几何形状与频率响应之间的关系.滤波器的几何形状在限定固定滤波器长度的情况下由阻带抑制最佳化来确定.用此方法能设计具有平坦的通带振幅和相位响应的滤波器.     

基于PDE的自适应各向异性图像配准方法研究

针对传统光流场配准模型会造成图像模糊和细节丢失的问题,提出了一种基于偏微分方程的自适应各向异性配准模型。新模型将具有自适应性的扩散滤波方法引入图像配准,定义具有图像结构保持能力的各向异性扩散函数作为模型的正则项;数据项采用作用于亮度常量假设的非二次惩罚函数以增加模型的稳健性。实验结果表明,新模型能够有效保持图像特征,实现对大脑等复杂图像的有效配准。     

一种改进型重复控制器的研究

提出一种新的改进型重复控制策略,克服了传统重复控制器内模使用过多数据存储空间的缺点.详细分析新型控制器的模型,给出控制器优化设计方法.在设计中加入电流内环,通过电感电流反馈来降低输出滤波器的谐振峰值,增加系统的稳定性,简化了重复控制器的设计.与传统直接重复控制器相比,去除了North滤波器,弥补了North滤波器谷点设计不精确的缺点.     

各向异性滤波在红外图像处理中的应用

为了在抑制噪声时尽可能保留图像边缘信息,提出一种自适应各向异性高斯滤波器设计方法．该方法由独立强度传播(IDS)模型决定滤波器的长轴尺度,由像素的邻域平滑度决定长短轴的比例,然后根据该处的灰度梯度方向自适应决定各向异性滤波器的长轴方向．仿真实验表明,提出的自适应各向异性滤波器具有很强的噪声抑制和边缘保持能力．     

空间自适应卷积核滤波红外弱小目标检测

为了减少复杂红外图像中平滑背景边缘的影响,将具有各向异性特性的PM扩散模型应用到红外弱小目标检测,提出了空间自适应卷积核滤波检测算法,并对扩散系数进行了优化。针对模型中扩散参数难以确定的问题,提出了一种利用Sobel边缘检测算子估计扩散参数的方法。滤波后采用信噪比(SNR,Signal Noise Ratio)和接受机工作特性(ROC,Receiver Operating Characteristic)曲线进行性能评价,实验结果表明,与PM扩散模型滤波和中值滤波相比,该算法有效抑制了边缘,大大提高了信噪比,提高了检测概率,降低了虚警概率,具有更好的性能。     

Image denoising via an adaptive weighted anisotropic diffusion

Multidimensional Systems and Signal Processing - This paper introduces an adaptive weighted anisotropic diffusion model for image denoising. A simple but efficient patch-based diffusivity function...     

Smoothing low-SNR molecular images via anisotropic median-diffusion

We propose a new anisotropic diffusion filter for denoising low-signal-to-noise molecular images. This filter, which incorporates a median filter into the diffusion steps, is called an anisotropic median-diffusion filter. This hybrid filter achieved much better noise suppression with minimum edge blurring compared with the original anisotropic diffusion filter when it was tested on an image created based on a molecular image model. The universal quality index, proposed in this paper to measure the effectiveness of denoising, suggests that the anisotropic median-diffusion filter can retain adherence to the original image intensities and contrasts better than other filters. In addition, the performance of the filter is less sensitive to the selection of the image gradient threshold during diffusion, thus making automatic image denoising easier than with the original anisotropic diffusion filter. The anisotropic median-diffusion filter also achieved good denoising results on a piecewise-smooth natural image and real Raman molecular images.     

各向异性扩散图像去噪现状研究

介绍了基于偏微分方程(Partial Differential Equations,PDE)各向异性扩散图像去噪的P&M数学模型及各种改进方法,以及引入结构张量的PDE去噪模型和冲击滤波PDE去噪模型,分析各种模型的优缺点,为扩散模型的设计提供了参考。揭示了各向异性扩散去噪与贝叶斯最大后验估计(MAP)去噪的内在联系,通过扩散系数的计算分析几类常用去噪模型的保边性能。阐述了一类特殊PDE去噪模型(总变分去噪模型)与小波阈值去噪之间的相关性,从而可以通过小波系数的范数近似求解一些特殊的变分问题,避免复杂的非线性求解过程。最后对各向异性扩散图像去噪的未来发展进行了展望。     

An edge-adapting Laplacian kernel for nonlinear diffusion filters

In this paper, first, a new Laplacian kernel is developed to integrate into it the anisotropic behavior to control the process of forward diffusion in horizontal and vertical directions. It is shown that, although the new kernel reduces the process of edge distortion, it nonetheless produces artifacts in the processed image. After examining the source of this problem, an analytical scheme is devised to obtain a spatially varying kernel that adapts itself to the diffusivity function. The proposed spatially varying Laplacian kernel is then used in various nonlinear diffusion filters starting from the classical Perona-Malik filter to the more recent ones. The effectiveness of the new kernel in terms of quantitative and qualitative measures is demonstrated by applying it to noisy images.     

Robust anisotropic diffusion

Relations between anisotropic diffusion and robust statistics are described in this paper. Specifically, we show that anisotropic diffusion can be seen as a robust estimation procedure that estimates a piecewise smooth image from a noisy input image. The "edge-stopping" function in the anisotropic diffusion equation is closely related to the error norm and influence function in the robust estimation framework. This connection leads to a new "edge-stopping" function based on Tukey's biweight robust estimator that preserves sharper boundaries than previous formulations and improves the automatic stopping of the diffusion. The robust statistical interpretation also provides a means for detecting the boundaries (edges) between the piecewise smooth regions in an image that has been smoothed with anisotropic diffusion. Additionally, we derive a relationship between anisotropic diffusion and regularization with line processes. Adding constraints on the spatial organization of the line processes allows us to develop new anisotropic diffusion equations that result in a qualitative improvement in the continuity of edges.     

基于非线性复扩散耦合冲激滤波器的图像放大算法研究简

为了提高放大算法的适应性,采用改进的非线性复扩散和自适应冲激滤波器,提出了一种图像放大方法。根据像素局部方差进行自适应改变扩散门限,扩散图像的虚部除以扩散时间以消除扩散时间的影响,特别是初期扩散近似线性扩散的特性,得到改进的复扩散模型耦合冲激滤波器进行无噪图像放大。对于噪声图像放大,根据像素局部方差进行自适应非线性复扩散,耦合局部方差约束的冲激滤波器增强模糊的图像边缘和细节。自适应非线性复扩散通过局部方差和图像二阶导数相结合分辨边缘和噪声,对噪声进行平滑的同时保持边缘,克服了复扩散不能分辨噪声和边缘的缺陷,同时保持复扩散保护斜坡结构,免除阶梯效应的优点。仿真实验验证了所提算法不仅对无噪图像有较好的放大效果,而且对一定范围的噪声图像也有较好的放大效果。     

Comprehensive treatment of moisture induced failure-recent advances

This paper describes a comprehensive treatment of moisture induced failure in integrated circuit (IC) packaging with emphasis on recent advances. This includes advanced technique for modeling moisture diffusion under dynamic boundary conditions such as experienced by packages during solder reflow, autoclave, and temperature-humidity cycling; advanced characterization technique for moisture sorption and diffusion properties of packaging materials including effect of edge diffusion on transverse diffusivity, anisotropic diffusivity in organic laminates, impact of non-Fickian sorption; advanced techniques for modeling vapor pressure during solder reflow; advanced techniques for modeling dynamic delamination propagation during solder reflow; interfacial fracture strength as a function of temperature and moisture; as well as plastic analysis of popcorn cracking.