Local pattern descriptor for SAR image classification

In this letter, a simple, yet very powerful local descriptor called local pattern descriptor (LPD) is proposed for synthetic aperture radar (SAR) images classification. The descriptor aims at exploiting the underlying properties of SAR image texture. Specifically, LPD consists of two parts: image quantization and statistical features extraction. The method of image quantization is based on recent local binary pattern. For an SAR image patch in a moving window, after quantization, different patterns can be obtained, which represent the local structures that exist in SAR image. Then, the statistical features extracted from the different patterns are concatenated to construct the LPD. Experiments on the TerraSAR-X image present that the proposed descriptor yields promising results for SAR image classification when compared to other widely used features.