Bayesian deconvolution method applied to experimental bidirectional transmittance distribution functions
Jan Audenaert, Frédéric Leloup, Guy Durinck, Geert Deconinck, Peter Hanselaer · Measurement Science and Technology · 2013
Optical simulations are a common tool in the development of luminaires for lighting applications. The reliability of the virtual prototype is strongly dependent on the accuracy of the input data such as the emission characteristics of the light source and the scattering properties of the optical components (reflectors, filters and diffusers). These scattering properties are characterized by the bidirectional scatter distribution function (BSDF). Experimental determination of the BSDF of the materials is however very sensitive to the characteristics of the measuring instrument, i.e. the dimensions of the illumination spot, the detector aperture, etc. These instrumental characteristics are reflected in the instrument function. In order to eliminate the influence of the instrument function the use of a Bayesian deconvolution technique is proposed. A suitable stopping rule for the iterative deconvolution algorithm is presented. The deconvolution method is validated using Monte Carlo ray tracing software by simulating a BSDF measurement instrument and a virtual sample with a known bidirectional transmittance distribution function (BTDF). The Bayesian deconvolution technique is applied to experimental BTDF data of holographic diffusers, which exhibit a symmetrical angular broadening under normal incident irradiation. In addition, the effect of applying deconvolved experimental BTDF data on simulations of luminance maps is illustrated.