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

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.