A High Autonomous Sea Front Detection Algorithm Based on SAR Data

Abstract

This paper has proposed a high autonomous sea front detection algorithm based on SAR data. Through the innovative introduction of empirical mode decomposition method, a good image de-trend and de-stripe effect is achieved. By introducing the calculation of the maximum interclass variance, the automatic conversion of binary images is realized; through the use of polynomial fitting method, the independent screening of front information is realized, and the continuity of front detection results is improved. After comparison, it is found that the new algorithm proposed in this paper has greatly improved detection accuracy and autonomy compared with the old algorithm. Finally, a SAR data of the GF-3 satellite on the west side of Taiwan Island is used to test the new algorithm proposed in this paper. The results show that the detection results are highly consistent with the original image in morphology, and the changes in frontal intensity are also very detailed, verifying the accuracy and autonomy of the new method.