A New Probability Distribution for SAR Image Modeling

This article introduces exponentiated transmuted-inverted beta (ET-IB) distribution, supported by a continuous positive real line, as synthetic aperture radar (SAR) imagery descriptor. It is an extension of the inverted important texture model for SAR imagery. The considered distribution approach increases flexibility baseline and new probabilistic useful in image applications. Besides introducing model, maximum likelihood method discussed parameter estimation. Numerical experiments are performed to validate use ET-IB amplitude Finally, three measured images referring forest, ocean, urban regions considered, performance proposed compared distributions usually this field. outperforms competitor models modeling terms some selected goodness-of-fit measures. results show that suitable descriptor can be used develop image-processing tools remote sensing