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Proceedings Paper

Superresolution of millimeter-wave images by iterative blind maximum-likelihood restoration
Author(s): Ho-Yuen Pang; Malur K. Sundareshan; Sengvieng A. Amphay
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Paper Abstract

The need for superresolution processing of images in multispectral seeker environments for facilitating smart munition guidance is being increasingly recognized, particularly when the sensor suite includes Millimeter-Wave (MMW) sensors with rather poor inherent resolution capabilities. Despite the technological breakthroughs being made in advanced radiometer designs, the inherent problems associated with diffraction limited imaging impose limitations on the resolution of acquired imagery thus necessitating efficient post-processing to achieve resolution improvements needed for reliable target detection, classification and aimpoint selection. Quantitative results from a recent project directed to superresolution processing of passive MMW images obtained from a 95 GHZ 1-foot diameter aperture radiometer are presented in this paper. The spectral extrapolation performance resulting from the implementation of an iterative Maximum Likelihood restoration algorithm is demonstrated and the robustness of the algorithm that facilities a blind implementation useful in scenarios characterized by an incomplete knowledge of sensor point spread function is highlighted.

Paper Details

Date Published: 27 June 1997
PDF: 12 pages
Proc. SPIE 3064, Passive Millimeter-Wave Imaging Technology, (27 June 1997); doi: 10.1117/12.277085
Show Author Affiliations
Ho-Yuen Pang, Univ. of Arizona (United States)
Malur K. Sundareshan, Univ. of Arizona (United States)
Sengvieng A. Amphay, Air Force Wright Lab. (United States)

Published in SPIE Proceedings Vol. 3064:
Passive Millimeter-Wave Imaging Technology
Roger M. Smith, Editor(s)

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