Mac Fhionnlaoich, N; Taylor, A; Guldin, S; (2019) Optimising Light Source Positioning for Even and Flux-Efficient Illumination. Journal of Open Source Software , 4 (37) , Article 1392. 10.21105/joss.01392.

Preview

Text 10.21105.joss.01392.pdf - Published Version Download (1MB) | Preview

Abstract

Designing imaging systems is a challenge faced by researchers in many fields including fluorescent imaging in life sciences and optical set-ups for automated capture of experimental data. The position of light sources within an imaging system has significant consequences for the downstream usability of the data it generates. Non-uniform illumination can contribute to low quality (or in some cases unusable) images, particularly so when illumination variation approaches or exceeds the sensitivity range of the capture device/camera. Similarly, low flux efficiency (i.e. ratio of flux through the imaging plane divided by the total flux from the source) will negatively affect the image acquisition and subsequent analysis. Often flux efficiency is sacrificed for illumination uniformity i.e. choosing to deliver less light to the target in order to keep the variation of light intensity low. Furthermore, the large number of possible positional configurations of a light source within an imaging system precludes manual optimisation. To tackle this issue, we offer a software for modelling the illumination profile for a given light source. The code can be easily adjusted to model a variety of positional configurations and rapidly calculates results for many thousands of variable combinations. We envisage the exploitation of this software for research as well as in the early stages of prototyping. For example, in the university environment where resources and time are limited. Furthermore, we demonstrate an approach by which a user can reduce the amount of possible multi-variable combinations down to the most viable options. This is performed using a modified convex hull approach in two-dimensions (optimising for two figures of merit, i.e. the total flux and the illumination variation). In principle, this method can be extended to n-dimensional space to include additional figures of merit for optimisation. Our model describes positions of a light source in Cartesian coordinates (x, y and z) relative to the centre of the illuminated area. The spatial region available for light source placement must be chosen by the user. In addition, the user defines a range of allowed angles of illumination in Polar coordinates (theta and phi) relative to the surface normal (see Figure 1a). Based on these user inputs, the software creates a set of illumination configurations. These are then tested for feasibility with regard to the requirements and limitations of the imaging device. This pre-filtering process can also be augmented by the user to suit the needs of their particular system.

Download activity - last month

Export as JSONCSVXML

Download activity - last 12 months

Export as XMLCSVJSON

Downloads by country - last 12 months

Export as JSONCSVXML

Archive Staff Only

View Item