Based On The Support Vector Machine SAR Image Enhancement And Classification

In recent years synthetic aperture radar gets to the rapid development, because of its high-resolution and all-weather characteristics. At the same time, modern computer technology and advanced digital signal processing technology had developed and SAR made wide applications in many areas, such as earth remote sensing, mapping, and the exploration of resources, and disaster forecasting, military command, as well as other aspects of the national economy.The coherent imaging method allows speckle noise in SAR images ,the speckle noise reduce the image quality and have an impact on the follow classification and identification applications, so the Speckle Reduction of the SAR image has been an important subject of synthetic aperture radar technical fields.Vapnik and others made a new generation system of machine learning methods on the basis of statistical theory. for excellent performance ,SVM has become the hot in the machine learning research , and in many areas have been successful applications,for example ,face detection, handwritten numeral recognition, text classification. As a new technology, SVM has further study in pattern recognizing.With the characteristics of radar data, first, the image must to through regression network processing in order to keep the edge image maximizing information and filtering noise , then according to the classified theory and technology work over classification method of particular type.Major study:(1)This paper analyses some of the basic speckle removal algorithm, In-depth study the support vector regression filtering technology network structure issues, and filtering network model used in SAR image enhancement processing. Through experiments proved that support vector regression filtering network's Practicability in the SAR image enhancement, for the next work provides a basis theory for classification.(2)To investigate the connection with kernel and SVM classification,choiced compounding kernel as SVM classification kernel , and used in SAR image classification . A large number of comparative experiments show that the compounding kernel SVM classification, not only improved performance of the classification, but also enhanced the accuracy of the classification in SAR images.