噪声背景中点目标检测的多比例法

A Multiscale Method for Detection of Point Target in Noisy Background

要把淹没在噪声背景中的运动点目标检测出来是一个十分困难的问题 .本文提出了一个基于多比例几何技术的运动目标检测新方法 .以高斯函数作为滤波核 ,用多比例方法构造了一个四维比例时空空间 .利用一阶几何特征导出了目标的运动约束方程 .基于目标图像的速度一致性和像素连接性 ,研究了解决运动检测与速度估计的方法 .描述了速度平面上约束直线聚类点或聚类区的粗精搜索算法 .给出了精确地搜索最优比例的精度度量 .提出的实验和比较结果 ,支持了这些研究 .

To detect a moving point target that is submerged in noisy background is a very difficult problem.A new approach to moving target detection based on multiscale geometric technique is proposed in this paper.A 4 D scale spatio temporal space is constructed by multiscale approach using Gaussian as a filtering kernel.A motion constraint equation for moving target is derived by the first order geometric features.A technique for solving the problem of motion detection and velocity estimation based on the velocity identity and pixel connectivity of the target image is described.A coarse fine search algorithm of the clustering point or area for constrainted straight lines on the velocity plane is outlined.An accuracy measure for precisely how to search an optimal scale of Gaussian is given.The experimant and comparison results are presented to support the research.