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.

Document Details

Document Type
Pub Defense Publication
Publication Date
Aug 26, 2020
Source ID
10.1364/ao.396496

Entities

People

  • C. C. Olson
  • Jonathan M. Nichols

Organizations

  • Office of Naval Research

Tags

Readers

  • Computational Modeling and Simulation
  • Image Processing and Computer Vision.
  • Sensor Fusion and Tracking Systems.