Introduction | Intro to stray light testing and normalized stray light | Outputs from Imatest stray light analysis | History Background | Examples of stray light | Root Causes | Test overview | Test factors | Test Considerations | Glossary Calculations | Metric image calculations | Normalization methods | Light source mask methods Instructions | High-level Imatest analysis instructions (Master and IT) | Computing normalized stray light with Imatest | Motorized Gimbal instructions Settings | Settings list and INI keys/values | Configuration file input Stray light (flare) documentation pages
Page Contents
This page provides description of the fundamental calculations that Imatest uses to generate stray light metric images.
Metric Image Calculations
At a high level, the measurement of stray light is very simple: normalize the digital numbers (DNs) of an image, while (optionally) masking out the image of the light source.
Transmission
The transmission stray light metric image calculation is to take the test image and divide it by a normalization factor.
\(\text{stray light} = \frac{\text{image [DN]}}{\text{normalization factor [DN]}} \)
With appropriate normalization factors, this is used to compute the Point Source Transmission (PST) [1] and Point Source Rejection Ratio (PSRR) [2] metrics.
For a “transmission” calculation, no stray light is indicated with a value of 0 and the worst possible stray light is indicated with a value of 1.
Attenuation
The attenuation stray light metric image calculation is to take a normalization factor and divide it by the test image.
\(\text{stray light} = \frac{\text{normalization factor [DN]}}{\text{image [DN]}}\)
With appropriate normalization factors, this is used to compute the flare attenuation metric proposed within IEEE-P2020 [3].
For an “attenuation” calculation, no stray light is indicated with a value of infinity, and the worst possible stray light is indicated with a value of 1.
Note: 0 is a valid image value (corresponding to no measurable stray light from the test configuration). When using the reciprocal calculation, these 0’s get transformed to infinity, which in turn, will reduce the meaningfulness of some summary metrics (e.g., mean, max).
References
[1] E. Fest. 2013. “Stray Light Analysis and Control”. SPIE Press. ISBN: 9780819493255. DOI: https://doi.org/10.1117/3.1000980.
[2] B. Bouce, et. al, 1974. “GUERAP II – USER’S GUIDE”. Perkin-Elmer Corporation. AD-784 874.
[3] IEEE-P2020 Automotive Image Quality Working Group. https://site.ieee.org/sagroups-2020/