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Proceedings Paper

An image sharpness metric for image processing applications using feedback
Author(s): Eric P. Lam; Christopher A. Leddy; Stephen R. Nash
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Paper Abstract

Some image processing applications require an image to meet a quality metric before performing processing on it. If an image is too degraded such that it is difficult or impossible to reconstruct, the input image may be discarded. When conditions do not exhibit time-invariant image degradations, it is necessary to determine how sharp an image is. In this paper, we present a metric that measures the relative sharpness with respect to a reference image frame. The reference image frame may be a previous input image or even an output frame from the image processor. The sharpness metric is based on analyzing edges. The assumption of this problem is that input images are similar to each other in terms of observation angle and time. Although the input images are similar, it cannot be assumed that all input images are the same, because they are collected at different time samples.

Paper Details

Date Published: 30 April 2007
PDF: 10 pages
Proc. SPIE 6543, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XVIII, 65430I (30 April 2007); doi: 10.1117/12.719083
Show Author Affiliations
Eric P. Lam, Thales Raytheon Systems (United States)
Raytheon Space and Airborne Systems (United States)
Christopher A. Leddy, Raytheon Space and Airborne Systems (United States)
Stephen R. Nash, Raytheon Space and Airborne Systems (United States)


Published in SPIE Proceedings Vol. 6543:
Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XVIII
Gerald C. Holst, Editor(s)

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