Regularization of noisy ISAR images containing extended features

We present a regularization method that employs a cross-entropy functional and which deals with the three issues of complex-valued data, prior information, and noise mitigation. The basic model of this approach is similar to that used in usual maximum a posteriori analysis and allows for a more general relationship between the image and its configuration entropy than that usually employed.