Texture Processing Of Synthetic Aperture Radar Data Using Second-Order Spatial Statistics

A method is presented for generating second-order spatial statistics (texture) from digital image data using the neighboring gray-level dependence matrix (NGLDM). Texture processing of a high-resolution airborne synthetic aperture radar image in an agricultural environment improved crop classification over the raw data. Classification of the large-number emphasis feature, based on the NGLDM (window size = 11 x 11, alpha = 24 and beta = 1), showed a 30.5% improvement in validation accuracy over the tonal data.