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A new AR-based technique to exploit SAR image correlation properties for rain forest classification

In this paper we develop a detector that exploits both variance and correlation properties of SAR images for the discrimination between regions with different characteristics. This detector is based on the generalized maximum likelihood approach applied to an autoregressive (AR) correlation model for the pixels of a homogeneous region. The application of the newly derived detector to C-band SAREX images of the Brazilian rain forest shows improved performance in the discrimination of clearings from forest.