Share Email Print

Proceedings Paper

Small-target detection in multispectral imagery with cyclic overlay processing
Author(s): Mark S. Schmalz; Wen-Chen Hu; Gerhard X. Ritter
Format Member Price Non-Member Price
PDF $17.00 $21.00

Paper Abstract

The detection of small, hostile targets in multispectral imagery is generally complicated by sensor noise, atmospheric obscurants, and spatial distortions induced by the point-spread function (PSF). Traditional methods for multispectral detection of small targets, such as signature- based discrimination predicated upon deterministic physical models, have not proven robust in the presence of camera noise at low light levels. The additional problem of target variability also confounds a signature-based approach. Due to time-dependent variations in illuminant spectra response, targets can appear to have different spectral properties at different times of day and under various weather conditions. In this paper, we discuss computationally efficient methods for locating targets that differ spectrally from their spatially adjacent backgrounds but are similar to features located elsewhere in the source image. In particular, we note that flicker effects can be produced in which target intensity appears to vary differently with background intensity. Such effects are produced computationally by cyclic overlay processing (COP), which sequentially displays monospectral band images to achieve different perceived flicker rates of target and background. When combined with knowledge about the human visual system (HVS), COP can be successfully used in conjunction with neighborhood operations to segment target regions in highly cluttered imagery. We emphasize the role of target-background contrast in potentiating flicker effects, and discuss algorithms for computing COP. Analyses emphasize computational cost and effectiveness of various COP filter configurations for detecting targets that are similar to, or partially obscured by, surrounding cover or earth. We also discuss the implementation of our algorithms on parallel processors, in particular, the parallel algebraic logic (PAC) architecture currently being implemented in cooperation with Lockheed- Martin and USAF Wright Laboratory. Our algorithms are written in image algebra, a rigorous, concise, inherently parallel notation that unifies linear and nonlinear mathematics in the image domain and has been implemented on a variety of parallel processors. Thus, our algorithms are both feasible and portable.

Paper Details

Date Published: 17 June 1996
PDF: 13 pages
Proc. SPIE 2758, Algorithms for Multispectral and Hyperspectral Imagery II, (17 June 1996); doi: 10.1117/12.243240
Show Author Affiliations
Mark S. Schmalz, Univ. of Florida (United States)
Wen-Chen Hu, Univ. of Florida (United States)
Gerhard X. Ritter, Univ. of Florida (United States)

Published in SPIE Proceedings Vol. 2758:
Algorithms for Multispectral and Hyperspectral Imagery II
A. Evan Iverson, Editor(s)

© SPIE. Terms of Use
Back to Top
Sign in to read the full article
Create a free SPIE account to get access to
premium articles and original research
Forgot your username?