Paper
19 May 1999 Spatio-temporal discrimination model predicting IR target detection
Author Affiliations +
Proceedings Volume 3644, Human Vision and Electronic Imaging IV; (1999) https://doi.org/10.1117/12.348461
Event: Electronic Imaging '99, 1999, San Jose, CA, United States
Abstract
Many image discrimination models are available for static imags. However, in many applications temporal information is important, so image fidelity metrics for image sequences are needed as well. Ahumada et al presented a discrimination model for image sequences. It is unusually in that it does not decompose the images into multiple frequency and orientation channels. This helps make it computationally inexpensive. It was evaluated for predicting psychophysical experiments measuring contrast sensitivity and temporal masking. The results were promising. In this paper we investigate the performance of the above-mentioned model of a practical application - surveillance with IR imagery. Model evaluation is based on two-alternative force choice experiments, using a staircase procedure to control signal amplitude. The observer is presented with two one-second- duration IR-image sequences, one of which has an added target signal. The observer's task is to guess which sequence contained the target. While the target is stationary in the image center, the background moves in one direction, simulating a tracking station in which the observer has locked on to the target. The results show that the model qualitatively, in four out of five cases, have the desired behavior.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Kjell E. Brunnstroem, Robert Eriksson, and Albert J. Ahumada Jr. "Spatio-temporal discrimination model predicting IR target detection", Proc. SPIE 3644, Human Vision and Electronic Imaging IV, (19 May 1999); https://doi.org/10.1117/12.348461
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Cited by 2 scholarly publications.
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KEYWORDS
Infrared imaging

Target detection

Visual process modeling

Eye models

Infrared detectors

Infrared radiation

Data modeling

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