Learned linear models for detecting watercraft in a maritime environment

Abstract

This work provides a new, to the best of our knowledge, approach to constructing linear models for object detection in a scene. Specifically, we use representative training data in order to estimate the parameters describing a generalized wavelet model for the express purpose of detecting the presence of maritime targets in a scene. The parameter estimates are taken as those that maximize the probability of detecting the targets for a fixed probability of false alarm. The approach is then demonstrated on a database of short-wave infrared imagery containing various watercraft. Results are then compared to some of the more standard wavelet bases used in detection applications.