Share Email Print
cover

Proceedings Paper

New methodology for predicting minimum resolvable temperature
Author(s): Richard Vollmerhausen; Van Hodgkin
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

The most common form of system performance check for thermal imagers is Minimum Resolvable Temperature (MRT). Viewing 4-bar patterns of various sizes, one at a time, generates an MRT plot. For each size of bar pattern, the MRT is the minimum temperature between bar and space that makes the pattern visible. Small MRT when viewing a large bar pattern indicates good system sensitivity, and small MRT when viewing a small bar pattern indicates good system resolution. Two problems make laboratory MRT difficult to predict. First, because MRT is supposed to represent the best achievable sensor performance, the operator is encouraged to change sensor gain and level for each bar pattern size. This means that the imager is not in a single gain state throughout the MRT measurement. Second, aliasing makes the MRT for sampled imagers difficult to predict. This paper describes a new model for predicting laboratory MRT. The model accounts for variation of the sensor gain during measurement. Also, the model includes the visual bandpass properties of human vision, permitting sampled imager MRT to be accurately predicted. These model changes result in MRT predictions significantly different from previous models. Model results are compared to laboratory measurements.

Paper Details

Date Published: 12 May 2005
PDF: 9 pages
Proc. SPIE 5784, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XVI, (12 May 2005); doi: 10.1117/12.609915
Show Author Affiliations
Richard Vollmerhausen, Consultant (United States)
Van Hodgkin, U.S. Army Night Vision and Electronic Sensors Directorate (United States)


Published in SPIE Proceedings Vol. 5784:
Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XVI
Gerald C. Holst, Editor(s)

© SPIE. Terms of Use
Back to Top