A new visual attention-based method for water detection in SAR images

Water detection in SAR images has been widely used in water area mapping and monitoring flooding [1] [2]. However, two challenges exist in water detection in SAR images. First, due to changeable ocean climate, radar backscatte strength varies in the different regions of the same water, which causes error detection. Second, it is difficult to distinguish water from low gray vegetation and road network.

[1]  Christof Koch,et al.  A Model of Saliency-Based Visual Attention for Rapid Scene Analysis , 2009 .

[2]  Fakhri Karray,et al.  A Probabilistic Model of Overt Visual Attention for Cognitive Robots , 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[3]  Lars Kaleschke,et al.  ERS-2 SAR image analysis for sea ice classification in the marginal ice zone , 2002, IEEE International Geoscience and Remote Sensing Symposium.

[4]  Patrick Le Callet,et al.  A coherent computational approach to model bottom-up visual attention , 2006, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[5]  Ning Ma,et al.  SAR Water Image Segmentation Based on GLCM and Wavelet Textures , 2010, 2010 6th International Conference on Wireless Communications Networking and Mobile Computing (WiCOM).

[6]  George K. I. Mann,et al.  An Object-Based Visual Attention Model for Robotic Applications , 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

[7]  Rajiv Kumar Nath,et al.  Water-Body Area Extraction from High Resolution Satellite Images-An Introduction , Review , and Comparison , 2010 .