Study of residents information extraction in SAR image based on texture features

Wenbo Wu, Lijing Bu
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引用次数: 1

Abstract

This paper focuses on the topic of extracting residential properties information based on texture features in low or moderate resolution SAR image, because the residential area has characters of high bright and regular texture in that scale image. Firstly, filtering the noises of the SAR image by using the FROST algorithm; secondly, obtaining a binary image which contains the residential information by threshold processing; thirdly extracting texture features based on the gray-level co-occurrence matrix and the texture features such as entropy, variance and correlation are selected according to actual situation, then the selected images are combined into a multiband image; Finally, the multi-band image multiplies the binary image and gets a new image, then classifying it by unsupervised classification, connecting the break points by using the morphology algorithm, a boundary of residential areas is obtained. As results, both the theoretical analyses and the experimental results indicate that this method is very efficient in extracting the residential information.
基于纹理特征的SAR图像居民信息提取研究
针对低、中分辨率SAR图像中居住区具有高亮度和规则纹理的特点,本文研究了基于纹理特征的住宅属性信息提取方法。首先,利用FROST算法对SAR图像进行噪声滤波;其次,通过阈值处理得到包含居住信息的二值图像;再次,基于灰度共生矩阵提取纹理特征,并根据实际情况选取熵、方差、相关性等纹理特征,将选取的图像组合成多波段图像;最后,将多波段图像与二值图像相乘得到新图像,进行无监督分类,利用形态学算法连接断点,得到居住区边界。理论分析和实验结果均表明,该方法能够有效地提取住宅信息。
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