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首页> 外文期刊>Geoscience and Remote Sensing Letters, IEEE >Multiscale Contour Extraction Using a Level Set Method in Optical Satellite Images
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Multiscale Contour Extraction Using a Level Set Method in Optical Satellite Images

机译：使用水平集方法的光学卫星图像多尺度轮廓提取

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摘要

This letter presents a novel coarse-to-fine level set method for contour extraction in optical satellite images. To distinguish objects from a background, the undecimated wavelet transform is firstly adopted to extract image features, and a homogeneity metric is defined to measure the variation of the features inside and outside contours. In addition, the weight distribution ratio is proposed to adaptively tune the relative weight of the features. Based on the homogeneity metric and the weight distribution ratio, a novel energy functional is developed to model a contour extraction problem, and in order to reduce the computation burden, a coarse-to-fine scheme is applied to progressively extract contours in finer scale, during which a contour position constraint is introduced to limit contours evolving in a small space around the candidate contours extracted in coarser scale. Extensive experiments have been carried out on optical satellite images to validate the proposed method.
机译：这封信提出了一种新颖的从粗到细水平集方法，用于光学卫星图像中的轮廓提取。为了将物体与背景区分开来，首先采用未抽取的小波变换提取图像特征，并定义了均匀性度量来度量特征在轮廓内外的变化。另外，提出了权重分配比以自适应地调整特征的相对权重。基于均一性度量和权重分布比，开发了一种新的能量函数来对轮廓提取问题进行建模，并且为了减轻计算负担，采用了从粗到精的方案以较小的比例逐步提取轮廓，在此期间，引入轮廓位置约束以限制轮廓以较小的比例在候选轮廓周围的较小空间内演变。已经对光学卫星图像进行了广泛的实验以验证所提出的方法。

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