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A new linear transfer theory and characterization method for image detectors. Part I: theory
Tore Niermann1, Axel Lubk, Falk Röder
1Institut für Optik und Atomare Physik, Technische Universität Berlin, Strasse des 17, Juni 135, 10623 Berlin, Germany. niermann@physik.tu-berlin.de
Ultramicroscopy
|April 3, 2012
Summary
A new theory models signal and noise transfer in image detectors, calculating pixel statistics and correlations. It introduces a noise spread function, offering a more complete noise characterization than traditional methods.
Area of Science:
- Physics
- Image Science
- Signal Processing
Background:
- Traditional image detector analysis often uses simplified models.
- Existing methods like point spread function capture average signal transfer.
- Noise characterization is often limited to specific conditions, like uniform illumination.
Purpose of the Study:
- To present a generalized linear transfer theory for image detectors.
- To enable pixelwise calculation of statistical moments and inter-pixel correlations.
- To introduce a novel method for characterizing noise transfer and generation.
Main Methods:
- Development of a generalized linear transfer theory.
- Application of the theory to calculate first and second statistical moments (mean, variance, covariance).
- Introduction and utilization of a noise spread function (NSF).
Main Results:
- The theory accurately calculates pixelwise statistical moments for arbitrary images.
- A noise spread function is defined, characterizing spatially resolved noise transfer and generation.
- Established noise metrics (noise power spectrum, detection quantum efficiency) are shown to provide incomplete noise information.
Conclusions:
- The generalized linear transfer theory provides a comprehensive framework for signal and noise analysis in image detectors.
- The noise spread function offers a more complete description of noise behavior compared to previous metrics.
- This approach enhances understanding of image quality and detector performance.
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