CAJ | 학술논문

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，提出了一种新的图像匹配方法，即基于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-TS201的红外图像目标匹配中，实验表明，此算法在保证匹配准确度的同时提高了系统的实时性。
기우회도상관적도상필배산법대광조변화민감，차계산량대，효솔저，이기우특정적도상필배산법결구복잡차재흔대정도상의뢰우특정제취적질량。위차，제출료일충신적도상필배방법，즉기우Sobel변연특정화소파변환적체추다모판쾌속필배산법。수선용Sobel산자제취변연특정；연후용소파변환대도상진행다척도분해；최후용본문제출적체추다모판쾌속산법부대집중료도상주요신식량적저빈부분진행호상관필배。장해산법응용우기우ADSP-TS201적홍외도상목표필배중，실험표명，차산법재보증필배준학도적동시제고료계통적실시성。
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.