Research On The Recognition Method Of Affected Target In Coastal Zone In The High Resolution Remote Sensing Image

Marine disasters have caused huge losses to the national economy and the safety of the coastal people as well as their property. Over the years, the acquisition of marine disaster information is completed by the local marine department through the way of field survey and report to superior department. However, this method requires a lot of manpower, material resources and time. With the rapid development of aerospace technology and sensor technology, the resolution of remote sensing image acquired by aerial camera is also getting higher, and it can obtain all-weather and real-time observation data. Therefore, the real-time monitoring of natural disasters by means of remote sensing has become one of the hot spots in the field of remote sensing.In this paper, we take affected targets in coastal zone as the research object and study the recognition method of them in the high resolution remote sensing images. First of all, we give a detailed introduction of three features which will used in the following chapters. Based on these three features, we propose a recognition method of typical targets in coastal zone using weighted probability strategy for multi-feature fusion. In the proposed method, SVM(support vector machine) classifier is employed to do the classification for every single feature. Then we calculate feature weight and certainty of SVM classification using the outputs form previous step. The final classification result is determined by the maximum posterior probability based on feature weight, certainty of SVM classification and SVM probability output.On the purpose of extracting accurately identifying results which are caused by linear target in the affected zone exist big differences and there is no fixed pattern of spectral changes, a linear affected target detection method is proposed which is based on the main direction of gradient. A single phase of remote sensing image combined with its historical vector information are used to calculate the uncertainty values of main direction of the gradient for each area under the detection window. The uncertainty values are compared with a threshold value to determine whether damages occurred in the region. In order to test the feasibility of the method, high resolution remote sensing images in two different regions are used to verify the test results. The results show that the method is simple and effective and it can accurately detect the damage zone of qualifying objectives.