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Related Experiment Video

Updated: Dec 25, 2025

Three-dimensional Super Resolution Microscopy of F-actin Filaments by Interferometric PhotoActivated Localization Microscopy iPALM

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Published on: December 1, 2016

Non-uniformity correction for medium wave infrared focal plane array-based compressive imaging.

Zimu Wu, Xia Wang

|April 1, 2020

Summary

This study addresses non-uniformity in medium wave infrared (MWIR) compressive imaging (CI) using focal plane array (FPA) sensors. A new calibration-based non-uniformity correction (NUC) method significantly improves image quality.

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Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities

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Evaluating Targeting Accuracy in the Focal Plane for an Ultrasound-guided High-intensity Focused Ultrasound Phased-array System

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Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities

Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities

Published on: October 27, 2023

Area of Science:

Optics and Photonics
Image Processing
Infrared Technology

Background:

Super-resolution imaging enhances image detail from low-resolution sensors.
Medium Wave Infrared (MWIR) imaging with Focal Plane Arrays (FPAs) is susceptible to non-uniformity, degrading image quality.
Compressive Imaging (CI) applied to MWIR FPA systems exacerbates non-uniformity issues.

Purpose of the Study:

Investigate the sources of non-uniformity in MWIR FPA CI systems.
Develop and validate a novel Non-Uniformity Correction (NUC) method tailored for MWIR FPA CI.
Enhance the image quality of super-resolved MWIR images obtained via CI.

Main Methods:

System modeling of MWIR FPA CI to understand non-uniformity origins.
Development of a calibration-based Non-Uniformity Correction (NUC) algorithm.
Experimental validation on an actual MWIR FPA CI system.

Main Results:

Identified specific sources of non-uniformity in both low-resolution captured and high-resolution reconstructed MWIR images.
The proposed calibration-based NUC method demonstrated superior performance compared to traditional methods.
Achieved significant improvement in image quality for MWIR FPA CI.

Conclusions:

The developed NUC method is effective and practical for MWIR FPA CI.
Understanding the particularities of non-uniformity in this system is crucial for image quality enhancement.
The findings offer significant guiding significance and practical value for MWIR imaging applications.