The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B6b. Beijing 2008 
5. CONCLUSIONS 
Based on the characteristic of water target, we proposed a 
method employing sequential nonlinear filter technique to 
extract water objects in SAR imagery, and make experiments 
using real SAR imagery. The results show that this approach 
can extract water objects in SAR imagery effectively and 
rapidly. For further research, we can calculate more 
characteristic parameters of region, and apply this algorithm to 
other low lightness objects extraction in SAR imagery. 
ACKNOWLEDGMENT 
This work was supported by the Space Foundation of China 
under grant No.0747-0540SITC2099-4. 
REFERENCES 
BI Jin-yuan; SONG Liang-tu, 2005. An Algorithm of Weak 
Target Detection from Remote Sensing ImageBased on 
Mathematic Morphology. Remote Sensing Information, pp.3-6. 
CHEN Yingying; SHAO Yongshe, 2006. A Radon Transform- 
Based Algorithm for the Detection and Matching of Airport 
Objects. Journal ofTongji University (Natural Science) . 
Easanuruk, S.; Mitatha, S.; Intajag, S.; Chitwong, S., 2005. 
Speckle Reduction Using Fuzzy Morphological Anisotropic 
Diffusion. In: 2005 Fifth International Conference on 
Information, Communications and Signal Processing. 12(06- 
09), pp.748-751. 
Pitas, I., 1996. State of the art of morphological and nonlinear 
digital image processing. In: proceedings of IEE Colloquium on 
Morphological and Nonlinear Image Processing Techniques. 
10, pp.1-4. 
Shih, F.Y.; Mitchell, O.R., 1998. Automated fast recognition 
and location of arbitrarily shaped objects by image morphology. 
In: Proceedings of Computer Society Conference on CVPR ’88. 
6 (5-9), pp.774-779. 
XIA Xin; LUO Dai-sheng; LUO Feng; LIN Hong-jin, 2005. An 
Efficient Method for Typical Target Feature Extraction and 
Recognition in SAR Images. Journal of Sichuan University 
(Natural Science Edition). 42(5), pp.969-973.