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Proceedings Paper

A new blur kernel estimator and comparisons to state-of-the-art
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Paper Abstract

This paper presents a simple, fast, and robust method to estimate the blur kernel model, support size, and its parameters directly from a blurry image. The edge profile method eliminates the need for searching the parameter space. In addition, this edge profile method is highly local and can provide a measure of asymmetry and spatial variation, which allows one to make an informed decision on whether to use a symmetric or asymmetric, spatially varying or non-varying blur kernel over an image. Furthermore, the edge profile method is relatively robust to image noise. We show how to utilize the concepts behind the statistical tools for fitting data distributions to analytically obtain an estimate of the blur kernel that incorporates blur from all sources, including factors inherent in the imaging system. Comparisons are presented of the deblurring results from this method to current common practices for real-world (VNIR, SWIR, MWIR, and active IR) imagery. The effect of image noise on this method is compared to the effect of noise on other methods.

Paper Details

Date Published: 9 May 2011
PDF: 19 pages
Proc. SPIE 8014, Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXII, 80140N (9 May 2011); doi: 10.1117/12.888126
Show Author Affiliations
Leslie N. Smith, U. S. Naval Research Lab. (United States)
James R. Waterman, U. S. Naval Research Lab. (United States)
K. Peter Judd, U. S. Naval Research Lab. (United States)


Published in SPIE Proceedings Vol. 8014:
Infrared Imaging Systems: Design, Analysis, Modeling, and Testing XXII
Gerald C. Holst; Keith A. Krapels, Editor(s)

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