Defect detection and response non-uniformity correction of a monocentric camera based on fiber optic relay imaging

Defect detection and response non-uniformity correction of a monocentric camera based on fiber optic relay imaging

Citation

The citation for the article, as provided in the source, is:

Xie, Dandan, Yawei Huang, and Changxiang Yan. "Defect Detection and Response Non-Uniformity Correction of a Monocentric Camera Based on Fiber Optic Relay Imaging." Optics Express 31, no. 14 (July 3, 2023): 22635. https://doi.org/10.1364/OE.493543.

Keywords

  • Monocentric camera
  • Fiber optic plate (FOP)
  • Defect detection
  • Non-uniformity correction
  • Space-based surveillance
  • Image sensor
  • Relay imaging
  • Otsu algorithm

Brief

This article describes a method for improving the imaging quality of monocentric cameras used in space-based surveillance by detecting and correcting defects in fiber optic plates (FOPs).

Summary

This 2023 Optics Express article, authored by Dandan Xie, Yawei Huang, and Changxiang Yan, focuses on enhancing the image quality of monocentric cameras used in space-based surveillance systems. These cameras utilize fiber optic plates (FOPs) for relay imaging, but imperfections within these FOPs can lead to defects and inconsistencies in the captured images.
Defect Detection:
  • The authors present a method for detecting defects in FOPs by analyzing images where the image sensor is intentionally saturated with light.
  • Defective areas, unable to transmit light, remain unsaturated and are thus identifiable.
  • This method proves more effective than the traditional Otsu algorithm, which is prone to misidentifying noise and dark filaments as defects.
Non-Uniformity Correction:
  • Even after addressing defects, inconsistencies in pixel response can arise from factors like light attenuation towards the edges of the image, variations in pixel response coefficients, and imperfections on optical surfaces.
  • The article details a correction process involving: 
    1. Linear Fitting: Establishing a relationship between input radiance and pixel output using a least squares method.
    2. Single Point Correction: Correcting individual pixel outputs based on the established linear relationship to achieve uniform illumination.
  • Experiments show this method reduces image non-uniformity from 10.01% to 0.78%.
Key Findings and Implications:
  • The proposed methods effectively identify and address FOP defects and pixel response non-uniformities in monocentric cameras.
  • These corrections result in clearer images, better suited for detecting faint space objects.
  • The techniques have potential applications in other optical fiber relay image transmission systems.
  • This summarization is based solely on the provided source.
Origin: https://opg.optica.org/oe/fulltext.cfm?uri=oe-31-14-22635&id=532167
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