一种基于数学形态学尺度空间的线性条带挖掘方法

A Mathematical Morphological Scale Space Based Method for Linear Belts Extracting

提出了一种线性条带挖掘方法LMSCMO。方法可分为两个主要部分 :首先 ,利用作者提出的基于数学形态学尺度空间的聚类算法MSCMO寻找到最合适的图像重分割尺度 ;其次 ,对此尺度下的分割结果进一步分割得到线性条带。LMSCMO是一种对“非纯粹直线”与噪声具鲁棒性的线性条带提取方法。

One spatial data mining method LMSCMO for linear belts extracting is proposed. LMSCMO can be divided into two basic steps: firstly, the most suitable re segmenting scale is found by our clustering algorithm MSCMO which is based on mathematical morphological scale space; secondly, the segmented result at this scale is re segmented to obtain the final linear belts. The authors declare that LMSCMO is a robust mining method to semi linear clusters and noises, which is validated by the successful extraction of seismic belts.