Rotational clutter metric

Salem M. Salem; Carl E. Halford; Steve K. Moyer; Matthew Gundy

doi:10.1117/1.3204234

1 August 2009 Rotational clutter metric

Salem M. Salem, Carl E. Halford, Steve K. Moyer, Matthew Gundy

Author Affiliations +

Optical Engineering, Vol. 48, Issue 8, 086401 (August 2009). https://doi.org/10.1117/1.3204234

Abstract

A new approach to linear discriminant analysis (LDA), called orthogonal rotational LDA (ORLDA) is presented. Using ORLDA and properly accounting for target size allowed development of a new clutter metric that is based on the Laplacian pyramid (LP) decomposition of clutter images. The new metric achieves correlation exceeding 98% with expert human labeling of clutter levels in a set of 244 infrared images. Our clutter metric is based on the set of weights for the LP levels that best classify images into clutter levels as manually classified by an expert human observer. LDA is applied as a preprocessing step to classification. LDA suffers from a few limitations in this application. Therefore, we propose a new approach to LDA, called ORLDA, using orthonormal geometric rotations. Each rotation brings the LP feature space closer to the LDA solution while retaining orthogonality in the feature space. To understand the effects of target size on clutter, we applied ORLDA at different target sizes. The outputs are easily related because they are functions of orthogonal rotation angles. Finally, we used Bayesian decision theory to learn class boundaries for clutter levels at different target sizes.

©(2009) Society of Photo-Optical Instrumentation Engineers (SPIE)

Citation Download Citation

Salem M. Salem, Carl E. Halford, Steve K. Moyer, and Matthew Gundy "Rotational clutter metric," Optical Engineering 48(8), 086401 (1 August 2009). https://doi.org/10.1117/1.3204234

Published: 1 August 2009

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