Open Set Recognition in SAR Images Using the Openmax Approach: Challenges and Extension to Boost the Accuracy and Robustness

The Openmax classifier has been recently introduced to tackle the open set recognition problem in the optical domain. In this paper, we first analyze different limitations of the Openmax classifier when applied to target recognition in synthetic aperture radar (SAR) images to study the occurrence of two potential errors: (1) recognizing a closed set image as an unknown and (2) not rejecting an open set image. Subsequently, we propose an extension to the Openmax approach to have a more robust and more accurate classifier. We evaluate the effectiveness of the proposed classifier using real SAR images from the MSTAR dataset.