苏腾飞,张圣微,李洪玉

• 1:内蒙古农业大学水利与土木建筑工程学院

摘要(Abstract)：

针对如何提升高分遥感影像超像素分割的精度与视觉效果问题,该文提出了一种基于种子区域生长(SRG)的超像素分割算法。该算法主要对超像素的生长过程进行了改进。在本文方法的超像素生长过程中,采用了一种充分利用光谱与形状信息的新度量标准,以有效搜索与种子适合合并的像素。该标准首先为斑块挑选在光谱上足够相似的像素,然后在这些像素中利用紧凑性异质性选择待合并的像素。为了定量评价算法的分割精度与视觉效果,定义了边界符合距离与平均斑块矩形度,并基于此发展了该文算法的参数选择策略。根据两景不同特点的高分遥感影像的超像素分割实验表明:本文方法在分割精度与视觉效果上均优于传统SRG与简单线性迭代算法。

关键词(KeyWords)： 种子区域生长;超像素;分割;高分遥感影像

Abstract:

Keywords:

基金项目(Foundation): 国家自然科学基金项目(51569017,51269014,61701265);; 内蒙古自然科学基金项目(2015MS0514);; 中国博士后科学基金面上项目(2015M572630XB)

作者(Author): 苏腾飞,张圣微,李洪玉

DOI: 10.16251/j.cnki.1009-2307.2018.08.020

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