Error estimation and smoothing of 2D illumination and chromaticity distributions

Methods for computing bin-by-bin error estimates of 2-D illumination and chromaticity distributions generated from Monte-Carlo raytracing data will be introduced, as well as algorithms for choosing the optimal number of bins based on the desired accuracy. Methods of improving the accuracy of such distributions will also be discussed, along with methods for smoothing these results for display purposes.