SVM- and MRF-based method for contextual classification of polarimetric SAR images

Classification of polarimetric SAR images based on the information provided by individual pixels cannot generally produce satisfactory results due to speckle. By introducing the spatial contextual information between adjacent pixels, a novel classification method, using support vector machine (SVM) and Markov random field (MRF), is proposed in this paper. It consists of two steps: first, a supervised pixelwise classification using SVM is applied to polarimetric SAR images; then, by means of MRF regularization, the spatial contextual information is introduced for refining the classification results obtained in the first step. The effectiveness of this method was demonstrated using a JPL/AIRSAR polarimetric SAR image. Compared with other three frequently used methods, better classification performance as well as less isolated pixels was observed, using the proposed method.