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Related Experiment Video

Updated: May 16, 2026

Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques
09:01

Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques

Published on: April 4, 2017

Platform motion blur image restoration system.

Stephen J Olivas1, Michal Šorel, Joseph E Ford

  • 1Photonic Systems Integration Laboratory, Electrical Engineering Department, University of California at San Diego, 9500 Gilman Dr., La Jolla, California 92093, USA. sjolivas@ucsd.edu

Applied Optics
|December 5, 2012
PubMed
Summary
This summary is machine-generated.

This study presents a new computational imaging system using optical position sensing detectors (PSDs) to correct motion blur in images. The system effectively reconstructs images degraded by spatially variant platform motion blur.

Related Experiment Videos

Last Updated: May 16, 2026

Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques
09:01

Gain-compensation Methodology for a Sinusoidal Scan of a Galvanometer Mirror in Proportional-Integral-Differential Control Using Pre-emphasis Techniques

Published on: April 4, 2017

Area of Science:

  • Computational Imaging
  • Image Processing
  • Optical Sensing

Background:

  • Platform motion blur affects airborne, space-based, and handheld imaging, especially in low light.
  • Correcting motion blur requires accurate point spread function (PSF) estimation, which is challenging due to spatial variance.

Purpose of the Study:

  • To introduce a novel computational imaging system for reconstructing images degraded by spatially variant platform motion blur.
  • To address the limitations of traditional motion blur correction methods.

Main Methods:

  • Incorporation of optical position sensing detectors (PSDs) with a conventional camera.
  • Utilizing PSDs to track light distributions and measure the PSF with high temporal resolution.
  • Generating a spatially variant PSF using multiple PSDs for image reconstruction.

Main Results:

  • Demonstrated a method to reconstruct images affected by spatially variant motion blur.
  • PSDs provide high temporal resolution for accurate PSF measurement.
  • The system enables effective correction of complex motion blur patterns.

Conclusions:

  • The developed computational imaging system offers a robust solution for motion blur correction.
  • This approach enhances image quality for applications sensitive to motion artifacts.
  • Optical position sensing detectors are crucial for capturing dynamic blur characteristics.