| 1. | Improved bit - allocation algorithm for anisotropic gaussian filter
一种改进的各向异性高斯滤波算法 |
| 2. | After the implementation of the 2 - d gaussian filters , blood vessels are clearly extracted from the background
经二维高斯滤波器的模板匹配后，血管从背景中显现出来，取得较令人满意的对比度和清晰度。 |
| 3. | 2 . based on studying canny operator and log operator , we take wavelet edge detection in allusion to smoothing image extremely and losing weak edge existed in gaussian filter
( 2 )在分析canny边缘检测算法和log边缘检测算法的基础上，针对高斯滤波器存在过度光滑图像和丢失缓变边缘的问题，采用基于小波变换的边缘检测算法。 |
| 4. | The main contents are as follows : 1 . review the theory and application of sequential monte carlo method , and discusse the filtering error counteraction problem by a nonlinear and non - gaussian filtering example . 2
主要内容包括: 1 .充分回顾了贯序蒙特卡罗方法的主要理论背景与应用现状,通过对一个非线性非高斯滤波算例的研究,讨论了滤波误差抵消问题。 |
| 5. | In this paper two algorithms have been proposed to track the low - elevation targets in the presence of multipath : the interacting multiple model ( imm ) algorithm and the non - gaussian filtering algorithm . two models are used in the interacting multiple model m ) algorithm
本文研究在多路径传播的条件下跟踪低空目标的滤波技术，给出了两种滤波算法：交互多模算法( imm )算法和非高斯滤波算法。 |
| 6. | Summarize the common image pre - processing methods and point out their merits and faults . discuss the boundary effect of gaussian low - pass filtering ( glpf ) . to improve it , the zero - order gaussian filtering for an open profile ( gfo ) is used
讨论了高斯低通滤波的边界效应,利用零阶开环高斯滤波算法,对高斯低通滤波进行了改进,使滤波图像在图像大小不改变的情况下,边缘处的滤波效果得到明显的改善。 |
| 7. | This method was divided into 4 steps : wiping out random noise by mean filter , reducing gaussian noise by gaussian filter , balancing brightness difference between stereo image pair through histogram equalization , and enhancing image edges and details by laplace sharpness
此方法分为4个阶段：用均值滤波去除随机噪声；用高斯滤波去除高斯噪声；用直方图均衡化法平衡立体图对间的亮度差异；用拉普拉斯锐化增强图像的边缘和细节。 |
| 8. | In the non - gaussian filtering algorithm , the measurement errors incorporating the multipath effects are modeled as the non - gaussian noise , and the filter are modified according to the score function . this algorithm , designed to track low - elevation targets , avoids the degrading of me performance because of ; . . c non - gaussian noise in the filter
在非高斯算法中，由于多径误差的影响，目标高度方向上的测量误差表现为非高斯噪声，首先建立观测噪声的非高斯模型，然后利用非高斯噪声下的滤波算法跟踪低空目标。 |
| 9. | It begins form the discussion the knowledge of the gaussian filter and the laplacian operator , which are the base of the marr method . and it is followed by the detail discussion of such as : the 2g （ laplacian of gaussian ) filter , the template log ( laplacian of gaussian ) , the meaning of laplacian of gaussian in human vision , edge detection and neurophysiology . with different template to different size of target , the small target can be separated from the background by this small infrared target detection method
从marr算法的理论基础? ?高斯平滑滤波器与拉普拉斯算子的相关知识以及Ｍ ａ ｒ ｒ的计算视觉理论基础开始，进行了2g ( laplacianofgaussian ，高斯?拉普拉斯)滤波器、 log ( laplacianofgaussian ，高斯?拉普拉斯)模板以及2g滤波器在人类视觉、边缘检测、边缘处理的物理意义以及神经生理学意义方面的分析讨论,提出了易于fpga ( fieldprogrammablegatearray ，现场可编程门阵列）实现的基于marr计算视觉的红外图像小目标检测方法。 |
| 10. | On this basis a nonlinear filtering technique of sequential monte carlo particle filter based on bayesian approach is emphatically disussed which the posterior distribution of the state variables can be represented by a set of weighted particles , so the method base advantages over the above algorithms in robustness and accuracy for nonlinear non - gaussian filtering problems
在此基础上重点论述了一种基于贝叶斯原理的序贯蒙特卡罗粒子滤波技术，该方法通过粒子的加权和表征后验概率密度，获得状态估值，在处理非线性非高斯系统的状态估计问题时精度逼近最优，鲁棒性更好。 |
