The contributions of this dissertation is listed below . aiming at existing defects of traditional beeline detection by hough transformation ( ht ) arithmetic , such as large storage space consuming , imprecise beeline detection effect and information loss of image feature pixels etc , we suggest two new beeline detection methods . ( 1 ) based on infinite symmetry exponential filter and its recursion arithmetic , new beeline detection methods can get exact direction of image edge pixels in advance , so it reduces highly the calculation quantity of the conventional ht , and improves the speed and the precision of beeline detection greatly 本论文的主要研究成果列举如下：针对传统直线检测霍夫变换( houghtransform ， ht )所存在的参数空间存储量大，直线检测不精确以及图像特征点信息丢失等缺点，提出两种新的直线段检测算法： ( 1 )提出一种基于无限对称指数滤波的ht直线段检测算法，在进行边缘检测的同时，提前精确定位边缘点的方向，减少了ht的运算量，提高了运算速度和检测精度，而且整体算法便于硬件的并行执行，使得实时处理成为可能。
First , it delves into the key technique of eis ? image registration , and presents an effective registration algorithm which is from coarse toprecise and form local to global . second , it applies recursive kalman filtering technique inmotion filtering of registration parameters and makes motion compensation for practical image . finally , it takes advantage of mosaicking to reconstruct undefined regions to avoid theubiquitous information missing and image degradation . this algorithm has high precision as wellas high speed 首先,对电子稳像中关键环节? ?图像配准技术进行了深入研究,给出一种由粗到精、由局部到全局的高效配准算法;接着,采用了递归kalman滤波技术对配准参数进行运动滤波并对实际图像进行运动补偿;最后,利用了图像拼接技术进行“无定义区”重建,避免了普遍存在的信息丢失和图像降质问题。
