Share Email Print
cover

Optical Engineering

Developing operational performance metrics using image comparison metrics and the concept of degradation space
Author(s): Carl E. Halford; Keith A. Krapels; Ronald G. Driggers; Eddie Burroughs
Format Member Price Non-Member Price
PDF $20.00 $25.00

Paper Abstract

. A technique for determining relative degradations from image metrics is presented along with a technique for predicting sensor performance from metrics. These techniques are illustrated with degradations of blur and noise in thermal imagery. These uses of metrics are depicted as mappings among a degradation space, an image quality metric space, and an operational performance space. This technique has utility in sampled imagery applications where input and output image comparison is possible, e.g., validation of an infrared scene projector (IRSP), testing image compression algorithms, image simulation, etc. Such applications have a known input image and a degraded output image. With the input image, one can characterize the output image in terms of its degradations relative to the input. The concept of a degradation space leads to developing an Operational Performance Metric (OPM) in terms of more traditional Image Quality Metrics (IQMs). The technique is illustrated using empirical results for human observers performing recognition tasks with thermal imagery in a degradation space of blur and noise.

Paper Details

Date Published: 1 May 1999
PDF: 9 pages
Opt. Eng. 38(5) doi: 10.1117/1.602048
Published in: Optical Engineering Volume 38, Issue 5
Show Author Affiliations
Carl E. Halford, Univ. of Memphis (United States)
Keith A. Krapels, Memphis State Univ. (United States)
Ronald G. Driggers, U.S. Army Communications and Electronics Command (United States)
Eddie Burroughs, U.S. Army Redstone Technical Test Ctr. (United States)


© SPIE. Terms of Use
Back to Top