采用金字塔分解的最小二乘影像匹配算法

最小二乘（ＬＳ）算法因其高精度而在影像匹配中被广为采用，但单纯的ＬＳ算法有收敛范围小，收敛速度慢等缺点。本文袖了结合金字塔分解ＬＳ匹配算法，此算法能大大增加单纯ＬＳ算法的收敛范围，提高匹配率，而运算时间与单纯ＬＳ法基本相当，并且保持了它的高精度，实验表明，此算法的精度高，匹配率高，收敛范围大，有相当的实用价值。

Least Square Matching Algorithm Using Pyramid Decomposing

Least Square (LS) algorithm is widely used in image matching owing to its high precision, but single LS algorithm has some drawbacks (i.e. slow speed and small converging range). So, an algorithm was realized in which pyramid decomposing and LS matching are combined. This algorithm can greatly enlarge convergence range and increase matching rate while spend roughly equal time and at the same time maintain the precision of LS algorithm. The experiment shows that this algorithm has high precision and matching rate, bigger converging range and faster speed when compared to a single LS algorithm. This algorithm is very practicable.