SAR Surface Ice Cover Discrimination Using Distribution Matching

• Main Author: Rashpal S. Gill
• Other Authors: The Pennsylvania State University CiteSeerX Archives
• Format: Text
• Language: English
• Subjects: Sea ice
• Online Access: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.142.3608; http://earth.esa.int/workshops/polinsar2003/papers/55_gill.pdf

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) Chi-Square (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