@CONFERENCE\{IMM2019-07124,
author = "A. A. Nielsen and H. Skriver and K. Conradsen",
title = "Generation of Sample Complex Wishart Distributed Matrices and Change Detection in Polarimetric {SAR} Data",
year = "2019",
month = "apr",
booktitle = "International Conference on Digital Image and Signal Processing (DISP)",
volume = "",
series = "",
editor = "",
publisher = "",
organization = "",
address = "",
note = "Matlab code in zip file. {SAR} input images to wishart\_change are images of the (row-wise) upper-right elements of the covariance or coherency matrix, e.g. for full polarimetry: a vector with nine real (i.e., non-complex) elements, namely [ShhShh* Re(ShhShv*) Im(ShhShv*) Re(ShhSvv*) Im(ShhSvv*) ShvShv* Re(ShvSvv*) Im(ShvSvv*) SvvSvv*].",
url = "http://disp-conference.org/Proceedings/Proceedings%20of%20DISP'19.pdf",
abstract = "The complex Wishart distribution is used to describe synthetic aperture radar (SAR) data in the so-called covariance matrix representation. We give a test statistic for detection of differences between two instances in this distribution and an associated probability measure. Generated complex Wishart distributed covariance matrices are used to show that this test statistic and the probability measure in situations with no differences follow the expected distributions.",
isbn_issn = "978-1-912532-05-6"
}