Regularization of noisy ISAR images containing extended features

We present a regularization method that employs a crossentropy functional and which deals with the three issues of complexvalued 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.