基于分水岭与多尺度相结合的影像分割方法

A High Resolution Image Segmentation Method of a Combination of Watershed and Multi-scale

分水岭分割是一种应用较广泛的影像分割方法,它能自动生成单像素宽度的封闭轮廓,但需要把影像分割成过多小区域,从而导致影像分割耗时且工作量大。本文就此提出一种分水岭和多尺度相结合的高分辨率影像分割方法。该方法首先运用分水岭方法对融合了亮度梯度和纹理梯度的综合梯度进行计算,然后将同质性度量值最小的区域对合并,最后结合改进区域邻接图进行区域合并。实验结果与基于分水岭和区域合并的影像分割算法得到的结果进行比较,证明该方法不仅能充分利用高分辨率遥感影像中地物的光谱、形状、纹理等特征,而且减少了计算时间。

Watershed segmentation is a widely used automatic scheme to generate close outlines.It might give rise to closed contour of single pixel width.Using this method the image needs to be divided into many small areas which leads to huge workload.This paper proposes a watershed and multi-scale comprehensive image segmentation method.Firstly,calculate the comprehensive gradient which merges the brightness gradient and the texture gradient by using watershed algorithm,then,merge the area of the smallest homogeneity measure（spectral,shape and texture homogeneity metric）,and the last,improve region adjacency graph.The experimental result is compared with watershed and region merging image segmentation algorithm,this method proves that it can not only take the advantage of high resolution remote sensing image features in the spectrum,shape,texture and other characteristics,and reduce the computational time.