Superpixel Segmentation with Boundary Constraints for Polarimetric SAR Images
Superpixel Segmentation with Boundary Constraints for Polarimetric SAR Images
复制标题
DOI：
10.1109/igarss.2018.8517849
复制
发表时间：
2018-07
期刊：
影响因子：
--
通讯作者：
Huiping Lin;Junliang Bao;Junjun Yin;Jian Yang
中科院分区：
文献类型：
--
作者：
Huiping Lin;Junliang Bao;Junjun Yin;Jian Yang
超像素分割在目标检测、图像分类等各种图像处理任务中有着广泛的应用。针对极化合成孔径雷达(PolSAR)图像，提出了一种基于新距离函数和超像素种子更新策略的超像素分割方法。我们使用预期数量的超像素来初始化超像素种子。然后，基于距离函数对像素进行迭代聚类，并根据更新策略更新超像素种子。当满足终止条件时，停止迭代，得到超像素。基于RADARSAT-2数据的实验结果表明，该方法是有效的，并在边界粘附性和紧致性之间取得了较好的折衷。
Superpixel segmentation has been commonly used in various image processing tasks such as object detection and image classification. In this paper, we propose a novel superpixel segmentation method based on a new distance function and superpixel seed updating strategy for polarimetric synthetic aperture radar (PolSAR) images. We initialize superpixel seeds with an expected number of superpixels. Then, we iteratively cluster the pixels based on the distance function and update the superpixel seeds based on the updating strategy. When the termination condition is reaches, we stop the iteration and obtain the superpixels. The experimental results based on RADARSAT-2 data demonstrate that our method is effective and achieves a better tradeoff between boundary adherence and compactness.