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High-Throughput Total Internal Reflection Fluorescence and Direct Stochastic Optical Reconstruction Microscopy Using a Photonic Chip

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Super-resolution for imagery from integrated microgrid polarimeters.

Russell C Hardie¹, Daniel A LeMaster, Bradley M Ratliff

¹Department of Electrical and Computer Engineering, University of Dayton, Dayton, Ohio 45459-0232, USA. rhardie@udayton.edu

|July 13, 2011

Summary

New super-resolution algorithms enhance microgrid polarimeter imagery by restoring undersampled polarization data. These advanced methods overcome aliasing artifacts, improving polarization content without reducing resolution.

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Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform

Time Multiplexing Super Resolving Technique for Imaging from a Moving Platform

Published on: February 12, 2014

Area of Science:

Optics and Photonics
Image Processing
Remote Sensing

Background:

Microgrid polarimeters use focal plane arrays (FPAs) with micropolarizers.
Subsampling FPA images for polarization channels reduces sampling frequency, causing aliasing artifacts.
Aliasing corrupts polarization information, necessitating advanced image restoration techniques.

Purpose of the Study:

To introduce novel multi-channel, multi-frame super-resolution (SR) algorithms for microgrid polarization imagers.
To address aliasing and other image degradations inherent in microgrid polarimetry.
To enhance polarimetric image restoration without sacrificing field of view or optical resolution.

Main Methods:

Development of the first multi-channel, multi-frame SR algorithms tailored for microgrid polarization imaging.
Implementation of SR methods that exploit correlations between polarimetric channels.
Utilizing a regularized least squares approach with an iterative solution and an adaptive Wiener filter-based SR method.

Main Results:

Demonstrated significant enhancement of polarimetric imagery using the new SR algorithms.
Showcased superior performance of multi-channel SR methods compared to single-channel approaches.
Successfully mitigated aliasing artifacts and other image degradations.

Conclusions:

The developed multi-channel SR algorithms effectively restore degraded microgrid polarization imagery.
These algorithms offer a viable solution for improving the quality of polarimetric data.
Exploiting inter-channel correlations significantly boosts the performance of SR in polarimetry.