21NRM01 HiDyn - Support for the standardisation of luminance distribution measurements for assessing glare and obtrusive light using high-dynamic-range imaging systems

• Research unit: METAS
• Project number: F-5116.30164

Key words (English)

- Luminance distribution
- High dynamic range (HDR)
- LEDr
- SI-traceability

Short description (English)

Luminance distribution measurements with high dynamic range (HDR) are required by various applications, e.g., measurement of new LED- or laser-based car headlights, obtrusive light and glare evaluation of indoor and outdoor scenes. Imaging luminance measurement devices (ILMD) and cost-effective RGB-based cameras are often used for such assessments. HDR measurements are achieved by post-processing image sequences, but standardization and uncertainty statements are usually absent. This JRP aims at developing procedures for providing with SI-traceability to HDR imaging measurement systems, a standardizing the determination of the instrument performance, including associated uncertainties, and at selecting an HDR algorithm adequate
for SI-traceable luminance measurements.

Project aims (English)

1. To develop luminance standards with high dynamic contrast pattern (covering at least 6 orders of magnitude) in order to characterise the dynamic range and spectral mismatch for different types of commercial instruments that are available for luminance distribution measurements (e.g., ILMD, RGB matrix sensor cameras). This should be based on the recommendations stated in CIE 232:2019 [1]
2. To model and validate HDR luminance measurements (including non-linearity, internal stray-light, and lens flare), with the objective of reproducibly determining the input data required for the models (average luminance, luminous surfaces, if required contrasts in the glare source, peripheral angle).
   To define the requirements for traceable instrumentation and to demonstrate the inter-comparability of HDR luminance measurements (in general and between different camera technologies), including the effect of its uncertainty on glare assessment.
3. To develop a harmonised metric (i.e. an algorithm) for (i) generating an HDR-luminance image from a sequence of multiple raw images and (ii) enabling traceability of relative images scaled to one or a few traceable spot measurements of the scene.