A RAPID METHOD FOR WATER TARGET EXTRACTION IN SAR IMAGE 
WANG Dong a , QINPing b 
a Dept. of Surveying and Geo-informatics, Tongji University, 
Shanghai 200092, China . - wangdong75@gmail.com 
b Dept. of Information, East China Sea Marine Prediction Center, State Oceanic Administrative, 
Shanghai 200082, China . - qinping00@gmail.com 
Commission VII, WG VII/2 
KEY WORDS: Synthetic Aperture Radar Imagery, Water Target, Automatic Recognition, Grey Morphology, Nonlinear Filter 
ABSTRACT: 
For the inherent speckles in SAR imagery, the processing of object extraction becomes more difficult. Using the traditional target 
extraction arithmetic for optical imagery, we can not get ideal result on SAR imagery. Water object in SAR imagery represents as 
some continuous region with low lightness and strong speckle noise. The traditional method to extract low lightness object can be 
implement by segment the imagery to binary imagery using a specify threshold. As the strong effect of the inherent speckle, how to 
gain an appropriate threshold is difficult. In this paper, the authors propose a sequential nonlinear filtering-based method to extract 
the water object in SAR imagery automatically. The experimental results using real SAR imagery show that our method can extract 
water objects in SAR imagery rapidly and accurately. 
1. INTRODUCTION 
Synthetic Aperture Radar (SAR) can generate images of the 
ground in all weather conditions including rain and fog at any 
time of day or night. It is a kind of important equipment for 
modem electric reconnaissance, widely used in civil and 
military. In recent years, SAR imaging has been rapidly gaining 
prominence in applications such as remote sensing, surface 
surveillance, and automatic target recognition. In the navigation 
application of military, extracting the airport, water region, road, 
etc. in SAR imagery is important to produce the reference 
imagery for matching with the real-time imagery. 
Different from some other remote sensing data, the SAR image 
do not obey the rule of projection but the rule of time of flight, 
and the SAR image data is most sensible on the geometric 
character of the surveyed object, not only on the macroscopical 
level, but also on the microscopical level. Both the natural 
character and the status of the object are important parameters 
of SAR image. In the application of SAR image automatic 
target recognition, it can seldom get good effect by using the 
traditional object extraction region segmentation operators, 
which are frequently used in optical images. A number of 
algorithms for SAR image segmentation and target extraction 
have been proposed. In the case of low contrast and strong 
interference, BI did the detection processing to extract some 
target with specific shape in the remote sensing images on the 
method based on the mathematical morphology theory (BI, 
2005) . In order to extract airport objects in real aperture radar 
image, CHEN employed radon transform technique to detect 
the runway and match the result with SAR imagery (CHEN, 
2006) . XIA proposed a method for object extraction and 
classification in SAR imagery using the threshold segmentation 
and character extraction techniques (XIA, 2005). 
In this paper, the authors proposed an algorithm based on grey 
morphology and sequential nonlinear filtering to extract the 
water objects in SAR imagery. 
2. WATER OBJECTS EXTRACTION BASED ON GREY 
MORPHOLOGY AND SEQUENTIAL NONLINEAR 
FILTERING 
In the SAR imagery, water area represents as the region which 
has low lightness. Now, using threshold segmentation method 
to transform the original image to binary image is mostly 
adopted to extract low lightness object. Affected by the intense 
inherent noise, choosing an appropriate threshold automatically 
is an important and sophisticated theme. Using the method 
based on hypothesis testing, after interaction many times, the 
threshold can be obtained. 
In this paper, based on the lightness of the water object and the 
spatial distribution characteristic of it, the method based on 
image segmentation threshold algorithm is not used. Employed 
the grey morphology and nonlinear filtering techniques, the 
author proposes a method to extract the water region in SAR 
image rapidly and effectively. 
From the basic gray-scale morphology operator, we can build 
up a sequential nonlinear filtering model to extract water 
objects in SAR imagery. 
Gray-scale dilation of f by b , denoted f ®b, is defined as 
(f®b)(s,t) = 
maxtf(s-x,t-y)+b(x,y) | (,s-x),(t-y) e £) f ; 
(x,y)eD b } 
(2.1) 
Gray-scale erosion of f by b , denoted f®b , is defined as