Wetland Classification of SAR Image based on the Polarization Characteristics Combination

Rapid and accurate classification of wetland features is the basis of accurate wetland monitoring. The key to improve the classification accuracy is to select the best polarization characteristics combination among many polarization characteristics. And in order to further study the influence of significant polarization characteristics of wetland features on classification results, a classification method based on the polarization decomposition characteristics of typical features in this area is proposed. In this method, the optimal polarization characteristics are selected and combined from a variety of polarization decomposition methods under the criteria of feature selection factors and so on by using the box plots, and then the classification is realized on this basis. Firstly, in order to simplify and reduce the speckle noises of PolSAR (Polimertice Synthetic Aperture Radar) image, the original four polarization images are processed by reciprocity, and the three polarization images after reciprocity are processed by multi-looks processing and Refined Lee filtering. Secondly, the data are decomposed into six kinds of polarization decompositions, such as Cloude-Pottierde decomposition and Paulide decomposition, and the polarization characteristics are extracted according to the decomposition results. Thirdly, the correlation between the above polarization characteristics and the scattering mechanism of typical features of Shuangtai Estuary wetland is analyzed in detail by using the box plots, Cloude-Pottier plane scatter plots and power mean scatter plots, and some polarization characteristics are selected under the criteria of feature selection factor, feature judgment factor, H/α plane, A/α plane, H/A plane, mean and standard variance. The selected polarization characteristics are combined. Finally, on the basis of the optimal polarization characteristics combination, the Support Vector Machine (SVM) classifier is designed to achieve the optimal classification of wetland features. Shuangtai Estuary, located at the estuary of Liaohe River in Panjin, Liaoning Province, is known as the "world's largest reed field". In order to verify the effectiveness of the optimal polarization characteristics combination, the C-band Radarsat-2 full polarization data in July, 2016 are utilized as experimental data. Through the qualitative and quantitative analysis of the proposed and the compared algorithm, the conclusions are as follows: the polarimetric entropy H, average alpha angle α and anisotropy A of the Cloude-Pottier decomposition, the single-bounce scattering of MCSM (Multiple-Component Scattering Model) decomposition, T33 of Pauli decomposition, the single-bounce and the double-bounce scattering of Yamaguchi3 decomposition are the optimal polarization characteristics on the one hand, and on the other hand, the optimal polarization characteristics combination can not only reduce the data redundancy and the calculation, and improve the classification efficiency, but also accurately represent the features and improve the producer's accuracy of each wetland category, the overall accuracy and kappa coefficient. Among them, the producer's accuracy of the wetland features has increased by 1% to 5%, the overall accuracyand kappa coefficient can reach 94.25% and 93.63% respectively. © 2021, Science Press. All right reserved.