Paper
27 June 1997 Superresolution of millimeter-wave images by iterative blind maximum-likelihood restoration
Ho-Yuen Pang, Malur K. Sundareshan, Sengvieng A. Amphay
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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.
© (1997) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ho-Yuen Pang, Malur K. Sundareshan, and Sengvieng A. Amphay "Superresolution of millimeter-wave images by iterative blind maximum-likelihood restoration", Proc. SPIE 3064, Passive Millimeter-Wave Imaging Technology, (27 June 1997); https://doi.org/10.1117/12.277085
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Cited by 6 scholarly publications.
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KEYWORDS
Point spread functions

Image processing

Sensors

Super resolution

Optical transfer functions

Algorithm development

Image resolution

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