基于增益曲线拟合的单星多波束干扰源定位

单星多波束干扰源定位的公式是基于卫星的信号增益曲线建立起来的,用理论公式描述信号增益曲线存在较大偏差,针对该问题提出用拟合函数代替理论公式。建立干扰源定位方程时,用实际增益点的拟合函数代替理论公式可以减小误差。对实际增益点采用先插值后拟合的方法,插值方法分别选用线性(Linear)插值和三次样条(Spline)插值,拟合函数分别采用傅里叶函数(Fourier)和多项式函数(Polynomial)。两种插值方法分别搭配两种拟合函数产生4种拟合方法,对比分析理论公式和4种拟合方法共5种算法的性能,分别比较与实际增益的偏差以及定位误差的大小,发现拟合方法优于理论公式,且线性插值加3阶傅里叶函数拟合方法性能最优。     

基于带参数的多结点样条表示的物体轮廓曲线匹配

针对三维碎片自动拼合中的碎片匹配问题,提出了一种新的轮廓曲线的表示和匹配方法.曲线的表示用带参数的多结点样条插值曲线拟合从碎片物体的轮廓线上提取的数据点,同时计算轮廓曲线上各个点的曲率、挠率和法矢.通过比较不同曲线特征段之间的全曲率,度量轮廓曲线之间的可匹配程度,利用法矢对相似度较高的轮廓曲线进行可匹配性验证,实现三维碎片的匹配.实验结果表明,该算法取得了较好的拟合和匹配效果,为基于轮廓线匹配的物体形状的拼接奠定了基础.     

矢量地图图形的多功能显示

本文着重研讨了一种根据计算机图形学中空间分布的型值点来构造插值样条曲线的造型方法。用此方法对矢量地图进行分层（分类）显示，并且能够对恢复后的矢显地图进行放大与缩小变换和特写显示。     

融合确定性信息和随机信息的插值方法研究

为了提高医学图像配准过程中的测度曲线光滑性和运算速度,本文利用图像的灰度概率分布作为确定性信息,同时利用非整数网格位置处的灰度随机性信息,定义了融合确定性信息和随机性信息的置信区域(DSCR);结合最近邻域插值法,提出了基于DSCR的最近邻域插值法(DSCRNN)。使用DSCRNN插值方法得到测度在整数平移位置处的值是准确无误差的。通过医学图像之间的刚体配准实验,从函数曲线、运算时间、抗噪鲁棒性和收敛性能方面对比分析了8种插值方法,结果表明,相对其它插值方法,DSCRNN插值方法在不牺牲插值速度的前提条件下可以提高归一化互信息(NMI)测度的收敛性能和抗噪声能力。     

短波多模馈电网络设计中的数据插值应用

馈电网络是短波多模多馈天线系统的重要组成部分,因此,馈电网络的设计是多模多馈天线系统设计的关键技术.互联网络子结构分析理论以网络参数数据化后形成的矩阵数据库为基础,利用矩阵数据库方法表示非均匀性子结构网络单元的网络参数.文中基于互联网络子结构分析方法,利用数据插值算法对馈电网络的传输线变压器S参数测量数据库进行了无缝化处理.插值结果表明,该算法能在满足一定的插值精度和插值效率的条件下对数据进行有效的插值处理.     

分形插值图像压缩的一种快速解码算法

一维分形插值图像编码是用插值点数据构造分形曲线来拟合数字图像的灰度曲线从而实现压缩。其解码过程就是求用插值点数据构造的迭代函数系统(IFS)的吸引子,由于图像数据以及分形插值迭代规律的特殊性,使得随机迭代算法和通常的固定迭代算法并不适用。本文设计了快速且节省内存的解码算法,并进行了复杂度分析。同时,本文的算法作为分形插值方法的一部分,同样可以用在分形插值法的其他应用领域。     

基于统计特征的彩色图像快速插值方法

本文首先阐述了基于统计特征的图像插值方法,该方法通过提取待插入像素所在区域的协方差矩阵和协方差向量,得出适应于边缘位置和方向的插值权重.为了把基于统计特征的图像插值方法应用于彩色图像插值领域,本文提出了以下措施以提高计算速度:仅对Y图像估计插值权重,并同时应用到R、G、B三个分量的插值;对边缘像素应用基于统计特征的图像插值方法,而对非边缘像素应用简单的双线性插值,即混合图像插值方法.这些措施提高了计算速度,并保证了图像质量.实验表明了该算法在计算速度和插值图像质量方面的有效性.     

太阳能电池工作特性户外监测系统研究

根据对光伏系统户外监测的需求,本文提出了结合恒定电压法与基于电阻矩阵增量导纳法的I-V曲线扫描算法,并阐述了样条插值曲线的重构方案。对上述算法的误差来源及复原曲线进行了分析,并根据具体的应用环境给出了该算法的具体实现。在此基础上给出了监测系统的架构设计及应用方法。依据该算法对实际监测的太阳能电池参数的准确性进行了仿真与实验。结果表明,本方案简便易行、扩展性好且具有较高的测量精度,可为户外光伏系统工作特性监测领域的设计提供一种较有竞争力的技术方案。     

统计推断约束下响应曲线的自适应Pade插值逼近

采用Pade插值技术，对计算获得的、稀疏的响应点值进行逼近，然后用获得的有理逼近式计算宽范围内响应曲线。把最小二乘法和插值技术结合起来，充分利用已有信息、达到最佳逼近的效果。同时自适应和精确地逼近响应曲线，引入了统计推断的办法。在统计推断的约束和判断下，实现了自适应的Pade插值逼近。为了检验方法的正确性，应用了混合插值技术，对FDTD法计算获得的、稀疏的RCS频率和角度响应曲线进行了逼近，在统计推断办法的约束和判断下，获得了很好的效果。     

基于三角网格上Coons曲面的图像缩放算法

针对传统插值算法在图像整体缩放中边缘区域易产生锯齿或模糊的现象,提出一种新型的图像缩放算法．将相邻像素形成的矩形区域进行三角剖分,根据待构造曲线段的位置关系及插值控制点的距离大小构造辅助的控制顶点,再利用相应的Bézier曲线插值图像构造的辅助控制点,最后以产生的Bézier曲线作为边界曲线,利用Coons曲面构造方法构造出退化的三角形曲面片进行边缘细节的强化。提出的方法可以很好地保持图像边缘细节,尤其在倾斜的边缘和尖角等处保持了更多的细节特征,使放大的图像有更好的效果。     

图像放大算法比较研究

图像放大算法的选择直接影响了图像放大的质量,为了更好地选择图像放大算法,从不同图像放大算法的原理出发,分别分析了最邻近点插值、双线性插值、双三次插值、三次B样条插值以及分形插值、小波插值、偏微分方程插值、领域交换内插算法的特点,并比较了它们的优、缺点;指出如何根据不同图像特征来选择不同算法以达到最优化效果;得出结合各种放大算法从而得到最好的放大效果是图像放大方法的发展方向。     

用于数字相机的CCD颜色插值算法研究

讨论了基于Bayer颜色滤波阵列的CCD图像传感器的几种颜色插值算法。从获得图像的质量、处理时间以及获得图像的信噪比等角度讨论了几种典型的插值算法，包括邻域插值、线性插值、相关线性插值、立方卷积插值和B样条插值。通过仿真实验研究，线性插值方法和相关线性插值方法在运算速度和图像信噪比方面都具有很好的品质，是数字相机插值的最佳选择。     

基于B-样条插值的分数阶模板的应用

数字图像的增强以及边缘检测是数字图像处理中的重要内容。根据B-样条函数插值公式,对图像灰度点像素值进行三次B-样条插值运算,提出了基于三次B-样条插值的分数阶增强模板以及分数阶CRONE边缘检测模板。通过对比实验表明,所设计的模板能根据对图像的需求而改变阶次,在图像增强方面能较好地提升图像边缘并且加强纹理细节,在边缘检测方面有良好的边缘定位能力,优于基于Sobel算子的传统方法。     

一种新的2kbit/s波形内插语音编码器

基于传统的波形内插语音编码模型,提出了一种新的2kbit/s语音编码方案。该方案在编码端去除了传统方法中复杂的对齐运算,在译码端用三次B样条插值取代传统的线性插值。慢渐变波形只量化低频分量,而快渐变波形用正交多项式拟合,并采用合成-分析技术对其进行矢量量化。DRT测试结果表明,该2kbit/s语音编码方法能获得高可懂度的重建语音。     

基于特征点能量优化的样条插值地形算法

针对在虚拟战场环境仿真中构建大规模地形,现有的计算机硬件条件无法进行实时处理,本文提出了一种对特征点用线性约束能量最小化方法反算控制点;用三次准均匀B样条曲线插值特征点生成B样条曲线,最后利用线动成面的原理生成B样条地形曲面。其中对偏差较大点通过增加新特征点的方法进行了自动修复。通过对实际高程数据值插值地形进行实验,得出运用该方法拟合的地形图更精确、更逼真。该算法主要用于对地形中重点关注区域进行地形重构,以提高局部地区的分辨率和逼真度。     

多帧超分辨率重建中的图像插值

为了实现多帧超分辨率重建,必须从图像序列中提取子像素信息,因此要求图像的配准精确到子像素级。本文提出了一种超分辨率重建中运动矩阵的构造方法。为了提高矩阵的构造精度,该方法引入图像插值,用性能好但计算量较小的三次插值算子实现插值运算,并比较了三种常用插值核的性能。实验结果表明,选择适当的插值函数不仅不会明显增加计算量,而且可以显著提高矩阵的构造精度,从而大大提高多帧超分辨率重建图像的质量。     

Comparison of interpolating methods for image resampling

When resampling an image to a new set of coordinates (for example, when rotating an image), there is often a noticeable loss in image quality. To preserve image quality, the interpolating function used for the resampling should be an ideal low-pass filter. To determine which limited extent convolving functions would provide the best interpolation, five functions were compared: A) nearest neighbor, B) linear, C) cubic B-spline, D) high-resolution cubic spline with edge enhancement (a = -1), and E) high-resolution cubic spline (a = -0.5). The functions which extend over four picture elements (C, D, E) were shown to have a better frequency response than those which extend over one (A) or two (B) pixels. The nearest neighbor function shifted the image up to one-half a pixel. Linear and cubic B-spline interpolation tended to smooth the image. The best response was obtained with the high-resolution cubic spline functions. The location of the resampled points with respect to the initial coordinate system has a dramatic effect on the response of the sampled interpolating function the data are exactly reproduced when the points are aligned, and the response has the most smoothing when the resampled points are equidistant from the original coordinate points. Thus, at the expense of some increase in computing time, image quality can be improved by resampled using the high-resolution cubic spline function as compared to the nearest neighbor, linear, or cubic B-spline functions.     

Construction of biological surface models from cross-sections imageprocessing

An approach improving on existing techniques is presented for blending cross-sections of biological objects to produce a polynomial surface model. As intermediate steps to the final surface skinning, representative data points on the cross-sections are selected for defining piecewise cubic B-splines providing an immediate reduction in storage and computational requirements for the contour representation of the objects. A mesh of quadrilateral patches is subsequently formed over adjacent cross-sections using bicubic B-spline surfaces which exhibit second parametric derivative continuity. The surface model provides a complete and robust representation with significant data reduction. The resulting algorithm is demonstrated using bone data for a human hand     

Survey: interpolation methods in medical image processing

Image interpolation techniques often are required in medical imaging for image generation (e.g., discrete back projection for inverse Radon transform) and processing such as compression or resampling. Since the ideal interpolation function spatially is unlimited, several interpolation kernels of finite size have been introduced. This paper compares 1) truncated and windowed sinc; 2) nearest neighbor; 3) linear; 4) quadratic; 5) cubic B-spline; 6) cubic; g) Lagrange; and 7) Gaussian interpolation and approximation techniques with kernel sizes from 1 x 1 up to 8 x 8. The comparison is done by: 1) spatial and Fourier analyses; 2) computational complexity as well as runtime evaluations; and 3) qualitative and quantitative interpolation error determinations for particular interpolation tasks which were taken from common situations in medical image processing. For local and Fourier analyses, a standardized notation is introduced and fundamental properties of interpolators are derived. Successful methods should be direct current (DC)-constant and interpolators rather than DC-inconstant or approximators. Each method's parameters are tuned with respect to those properties. This results in three novel kernels, which are introduced in this paper and proven to be within the best choices for medical image interpolation: the 6 x 6 Blackman-Harris windowed sinc interpolator, and the C2-continuous cubic kernels with N = 6 and N = 8 supporting points. For quantitative error evaluations, a set of 50 direct digital X rays was used. They have been selected arbitrarily from clinical routine. In general, large kernel sizes were found to be superior to small interpolation masks. Except for truncated sinc interpolators, all kernels with N = 6 or larger sizes perform significantly better than N = 2 or N = 3 point methods (p < 0.005). However, the differences within the group of large-sized kernels were not significant. Summarizing the results, the cubic 6 x 6 interpolator with continuous second derivatives, as defined in (24), can be recommended for most common interpolation tasks. It appears to be the fastest six-point kernel to implement computationally. It provides eminent local and Fourier properties, is easy to implement, and has only small errors. The same characteristics apply to B-spline interpolation, but the 6 x 6 cubic avoids the intrinsic border effects produced by the B-spline technique. However, the goal of this study was not to determine an overall best method, but to present a comprehensive catalogue of methods in a uniform terminology, to define general properties and requirements of local techniques, and to enable the reader to select that method which is optimal for his specific application in medical imaging.     

基于B—样条插值建立高速IC中互连系统瞬态响应的数值模型

本文基于B－样条插值提出了一种分析高速互连线瞬态响应的新的数值模型。算例分析表明,本文提出的新模型具有很高的计算精度和计算效率。