融合图像灰度信息与边缘特征的快速匹配算法

基于灰度相关的图像匹配算法对光照变化敏感，且计算量大，效率低，而基于特征的图像匹配算法结构复杂且在很大程度上依赖于特征提取的质量。为此，本文提出了一种基于Sobel边缘特征和小波变换的递推多模板快速匹配算法。首先用Sobel算子提取边缘特征；然后用小波变换对图像进行多尺度分解；最后用本文提出的递推多模板快速算法仅对集中了图像主要信息量的低频部分进行互相关匹配。将该算法应用于基于ADSP-S201的图像制导系统中，实验表明，此算法在保证匹配准确度的同时完全能达到系统实时性要求。 

Fast Image Matching Algorithm Based on Gray and Edge Features

The image matching algorithm based on gray-scale is sensitive to illumination changes, large in computation, and its efficiency is very low. The matching algorithm based on feature is complex and relies heavily on the quality of feature extraction. This paper presents a new image matching algorithm. It is a fast matching algorithm based on Sobel edge features, the wavelet transform, recursive plan and multi-template. First, using Sobel operator to extract edge features; second, using wavelet transform to decompose the image in multi-scale; last, using the recursive plan and multi-template method proposed in this paper to match with the low-frequency part which includes the main information of the image. The algorithm is applied in the midcourse guidance system based on the ADSP-TS201. The experiment shows that this algorithm not only ensures the matching accuracy but also improves the system’s real time.