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Related Experiment Video

Updated: Jul 6, 2026

Sample Drift Correction Following 4D Confocal Time-lapse Imaging

Sample Drift Correction Following 4D Confocal Time-lapse Imaging

Published on: April 12, 2014

Scene-based nonuniformity correction with video sequences and registration.

R C Hardie¹, M M Hayat, E Armstrong

¹Department of Electrical and Computer Engineering and the Electro-Optics Program, University of Dayton, 300 College Park, Dayton, Ohio 45469-0226, USA. rhardie@engr.udayton.edu

|March 14, 2008

Summary

This summary is machine-generated.

A new scene-based algorithm corrects array detector nonuniformity by registering image frames. This method estimates true scene values and detector parameters for accurate image correction with low computational cost.

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Area of Science:

Image processing
Detector physics

Background:

Array detectors suffer from pixel-to-pixel nonuniformity, causing fixed-pattern noise.
Accurate image data is crucial for various scientific and imaging applications.

Purpose of the Study:

To introduce a novel scene-based nonuniformity correction algorithm for array detectors.
To address fixed-pattern noise caused by detector pixel variations.

Main Methods:

The algorithm registers a sequence of observed frames to identify detectors observing the same scene irradiance.
It averages detector outputs to estimate true scene values.
Curve fitting is employed to estimate individual detector response parameters for correction.

Main Results:

Demonstrated effective nonuniformity correction using visible and infrared imagery.
Validated the algorithm's performance with simulated and real nonuniformity.
Showcased simplicity and low computational complexity.

Conclusions:

The developed algorithm provides an effective and computationally efficient solution for array detector nonuniformity correction.
The method is applicable to various imaging scenarios, including those with low-to-moderate nonuniformity levels.