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Published on: February 12, 2013
Scene-based nonuniformity correction technique that exploits knowledge of the focal-plane array readout architecture
Balaji Narayanan1, Russell C Hardie, Robert A Muse
1Department of Electrical and Computer Engineering, University of Dayton, Dayton, Ohio 45469-0226, USA. narayaba@notes.udayton.edu
Applied Optics
|July 13, 2005
Summary
This study introduces a novel algorithm to correct spatial fixed-pattern noise in infrared imagers. The method effectively reduces nonuniformity from detectors and electronics using a staged approach, requiring minimal frames for high-quality infrared image correction.
Area of Science:
- Infrared Imaging Technology
- Image Signal Processing
- Optical Engineering
Background:
- Spatial fixed-pattern noise is a significant challenge in infrared imagers.
- Nonuniform responses from photodiodes and readout electronics cause image degradation.
- Existing correction methods may require extensive calibration or computational resources.
Purpose of the Study:
- To develop and validate a novel, scene-based nonuniformity correction algorithm for infrared imaging systems.
- To address aggregate nonuniformity arising from both focal plane array detectors and readout electronics.
- To achieve high-quality image correction with reduced computational complexity and frame requirements.
Main Methods:
- A two-stage correction approach is proposed: first, correcting readout amplifier nonuniformity based on system architecture.
- Second, correcting detector nonuniformity using a nonlinear filter-based method.
- Algorithm performance is evaluated using simulated and real infrared data.
Main Results:
- The proposed algorithm effectively reduces spatial fixed-pattern noise in infrared imagery.
- Quantitative analysis shows improvements in mean absolute error and signal-to-noise ratio.
- The method demonstrates efficacy on both simulated and real infrared data.
Conclusions:
- The novel staged algorithm provides an effective solution for infrared imager nonuniformity correction.
- The algorithm's ability to achieve high-quality corrections with few frames is a key advantage.
- This approach offers a practical method for enhancing infrared image quality in various applications.
