CAJ | 학술논문

针对不同尺度地物的分割需求，提出了一种 k 均值聚类引导的多尺度分割优化方法。首先对原始影像进行小尺度分割和 k 均值聚类，然后利用 k 均值聚类结果引导对象合并，在合并过程中利用Otsu 阈值方法自动选择 k 均值聚类的影响因子，最终得到适应不同尺度地物的分割结果。以 FNEA 多尺度分割方法为例，利用模拟数据和真实的 GeoEye-1影像数据进行相关试验，目视和定量评价表明本文方法能够得到适宜不同尺度地物的高质量分割结果。
침대불동척도지물적분할수구，제출료일충 k 균치취류인도적다척도분할우화방법。수선대원시영상진행소척도분할화 k 균치취류，연후이용 k 균치취류결과인도대상합병，재합병과정중이용Otsu 역치방법자동선택 k 균치취류적영향인자，최종득도괄응불동척도지물적분할결과。이 FNEA 다척도분할방법위례，이용모의수거화진실적 GeoEye-1영상수거진행상관시험，목시화정량평개표명본문방법능구득도괄의불동척도지물적고질량분할결과。
In order to adapt different scale land cover segmentation,an optimized approach under the guidance of k-means clustering for multi-scale segmentation is proposed.At fi rst,smal l scale segmentation and k-means clustering are used to process the original images;then the result of k-means clustering is used to guide objects merging procedure,in which Otsu threshold method is used to automatical ly select the impact factor of k-means clustering;final ly we obtain the segmentation results which are appl icable to different scale objects.FNEA method is taken for an example and segmentation experiments are done using a simulated image and a real remote sensing image from GeoEye-1 satel l ite,qual itative and quantitative evaluation demonstrates that the proposed method can obtain high qual ity segmentation results.