CLUTTER CLASSIFICATION BASED ON A CORRELATED NOISE MODEL

The author extends the analysis of correlated texture classification in coherent imaging. The author investigates the variation of the accuracy with which the texture parameters can be determined and demonstrates that the previous model for the fitting process is inadequate. The author proposes a suitable modification to the theoretical model and compares predictions with simulation. Finally the author compares the results of texture classification based on parameter fitting with theory assuming independent normal distributions for the noise in the individual parameters.