Sar Surface Ice Cover Discrimination Using Distribution Matching

Discrimination between open water and sea ice in SAR imagery can still pose a problem to the ice analysts during manual interpretation. To help them in this task, new algorithm have been tested which is based on the user first manually identifying a particular surface type in a SAR image (e.g., open water area or sea ice of particular concentration or ice type) then the program will automatically determine similar regions in the remainder of an image. The algorithm is based on matching the statistics of the known and unknown regions using either (a) Kolmogorov-Smirnov (KS), or (b) ChiSquare (CS) distribution matching test. The main advantage in using these distribution matching tests is that the knowledge of the probability distribution functions (pdf) of the regions are not needed. Both KS and CS tests determine whether the two data sets belong to the same or different, yet undetermined, distributions. The main difference between KS and CS tests is that they are valid for un-binned and binned data respectively. The KS and CS were tested on the amplitude SAR image and the image products: (a) Power-to-Mean Ratio (PMR), and (b) Gamma-pdf which are computed from it. Both PMR and Gamma-pdf are useful tools for discriminating between open water and sea ice type in SAR images. The results presented in this article shows that the KS test is efficient (both reliable and computationally fast) at identifying similar surface types. It performed best with the amplitude data and Gamma-pdf while results using the PMR images were more prone to ambiguities. CS test did not perform as well as the KS test. This is because the data first has to be arbitrarily binned which results in some information being inevitably lost. It was also found to be many times slower to run on the computer. For these reasons it was decided not to use the CS test for matching known and unknown regions in a SAR image. The information obtained using the KS tests can be considered as the ‘best statistical guess’ during situations when the ice analysts have difficulty in interpreting parts of a SAR image. Keyword: Sea ice, RADARSAT, distribution matching, Kolmogorov-Smirnov test, Chi-Square test, Greenland.