SAR classification and polarimetric fusion

Andrew Hauter; Kuo-Chu Chang; Sherman Karp

doi:10.1117/12.242054

10 June 1996 SAR classification and polarimetric fusion

Andrew Hauter, Kuo-Chu Chang, Sherman Karp

Proceedings Volume 2757, Algorithms for Synthetic Aperture Radar Imagery III; (1996) https://doi.org/10.1117/12.242054
Event: Aerospace/Defense Sensing and Controls, 1996, Orlando, FL, United States

Abstract

The problem of target classification using synthetic aperture radar (SAR) polarizations is considered form a Bayesian decision point of view. This problem is analogous to the multi-sensor problem. We investigate the optimum design of a data fusion structure given that each classifier makes a target classification decision for each polarimetric channel. Thought the optimal structure is difficult to implement without complete statistical information, we show that significant performance gains can be made even without a perfect model. First, we analyze the problem from an optimal classification point of view using a simple classification problem by outlining the relationship between classification and fusion. Then, we demonstrate the performance improvement by fusing the decisions from a Gram Schmidt image classifier for each polarization.

Citation Download Citation

Andrew Hauter, Kuo-Chu Chang, and Sherman Karp "SAR classification and polarimetric fusion", Proc. SPIE 2757, Algorithms for Synthetic Aperture Radar Imagery III, (10 June 1996); https://doi.org/10.1117/12.242054

ACCESS THE FULL ARTICLE

INSTITUTIONAL
Select your institution to access the SPIE Digital Library.

SELECT YOUR INSTITUTION

PERSONAL
Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.

PERSONAL SIGN IN

No SPIE Account? Create one

PURCHASE THIS CONTENT

SUBSCRIBE TO DIGITAL LIBRARY

50 downloads per 1-year subscription

Members: $195

Non-members: $335 ADD TO CART

25 downloads per 1 - year subscription

Members: $145

Non-members: $250 ADD TO CART

PURCHASE SINGLE ARTICLE

Includes PDF, HTML & Video, when available