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### 基于G0分布的SAR图像水边线提取方法

1. 辽宁工程技术大学测绘与地理科学学院遥感科学与应用研究所,辽宁 阜新 123000
• 收稿日期:2016-09-20 修回日期:2016-11-26 出版日期:2017-07-20 发布日期:2017-07-20
• 作者简介:

作者简介：赵泉华（1978-）,女,河北承德人,博士,副教授,博导,主要研究方向为随机几何、空间统计学、模糊集理论等在遥感图像建模、解译及其在海洋环境遥感中的应用。E-mail:zhaoquanhua@lntu.edu.cn

• 基金资助:
国家自然科学基金（41301479、41271435）、辽宁省自然科学基金（2015020090）

### G0 Distribution Based on Water Line Extraction from SAR Image

Quanhua Zhao(), Guangchen Hu, Yu Li

1. Institute for Remote Sensing Science and Application, School of Geomatics, Liaoning Technical University, Fuxin 123000, Liaoning, China
• Received:2016-09-20 Revised:2016-11-26 Online:2017-07-20 Published:2017-07-20
• Supported by:
National Natural Science Foundation of China (41301479, 41271435),Natural Science Foundation of Liaoning Province(2015020090)

Abstract:

The water line is the demarcation line between land and sea areas. It is important interaction zone for global ecosystem conservation. As a result, it is vital that the rapid, accurate, real-time extraction of water line. Remote sensing solutions using Synthetic Aperture Radar (SAR) are playing an increasingly important role in monitoring water line and have getted much more attention from scholars and related department around the world. The sensor has two types: satellite SAR and airborne SAR. Satellite SAR has many advantages, for instance wide range observation, timely data available and all weather operation. As a result, it is a most suitable sensor for monitoring water line in marine environments. At present, the commonly used satellite SAR sensors for this purpose including Seasat SAR, Jers-1 SAR, Sentinel-1 SAR, and so on. In the SAR images, water line usually shows the edge characteristic, so the edge detection based algorithms are the most commonly used in coastline extraction. The classical edge detection operators including Canny operator, Sobel operator, Roberts operator, Prewitt operator and Laplacian operator, and so on. The operators have some advantages such as simple, fast speed, but they always effected by speckle noise inherent in SAR images, as a result, they can not obtain accurate water line results. So noise is a major issue for the task of boundary detection by the SAR images. Instead of combating the noise, we use a technique for boundary detection in SAR images based on the statistical properties of speckled data. The G0 distribution is a special form of G model, its parameters are very sensitive to the surface roughness and succeeds in characterizing a wide range of areas as sea, mountain chain and urban areas in speckled images. And the parameters required for boundary detection is extracted with moment estimation. Moreover, relative to G distribution, G0 distribution does not include the complex Bessel function, and is a kind of simple statistical distribution model with less parameter. According to the estimated parameters of G0 distribution, the marine and land areas can accurately be separated. In order to extract the water linefrom SAR image, a G0 distribution based algorithm is proposed in the article. First, the domain of SAR image is divided into a set of sub-blocks with the same size, and the grayscales of pixels in each sub-block are assumed to be identical and independent G0 distribution. The roughness of each sub-block and scatter shot parameters of the distribution are obtained with moment estimation. By thresholding the roughness parameter, the rough sea area can be divided, and then its geometric center is determined. On the rays started at the geometrical center, the cut-off points between sea and land are located with likelihood function. Consequently, the water line is formed by linking all the cut-off points. To prove its feasibility, a process of water line extraction has been tested with simulated and real SAR images by the method. Qualitative and quantitative results show that the proposed method can extract water line from SAR image effectively and efficiently.

• TP79