Photorealistic rendering involves the numeric resolution of physically accurate light/matter interactions which, despite the tremendous and continuously increasing computational power that we now have at our disposal, is nowhere from becoming a quick and simple task for our computers. This is mainly due to the way that we represent objects: in order to reproduce the subtle interactions that create detail, tremendous amounts of geometry need to be queried. Hence, at render time, this complexity leads to heavy input/output operations which, combined with numerically complex filtering operators, require unreasonable amounts of computation times to guarantee artifact-free images. In order to alleviate such issues with today's constraints, a multiscale representation for matter must be derived.

In this thesis, we derive such a representation for matter whose interface can be modelled as a displaced surface, a configuration that is typically simulated with displacement texture mapping in computer graphics. Our representation is derived within the realm of microfacet theory (a framework originally designed to model reflection of rough surfaces), which we review and augment in two respects. First, we render the theory applicable across multiple scales by extending it to support noncentral microfacet statistics. Second, we derive an inversion procedure that retrieves microfacet statistics from backscattering reflection evaluations. We show how this augmented framework may be applied to derive a general and efficient (although approximate) down-sampling operator for displacement texture maps that (a) preserves the anisotropy exhibited by light transport for any resolution, (b) can be applied prior to rendering and stored into MIP texture maps to drastically reduce the number of input/output operations, and (c) considerably simplifies per-pixel filtering operations, resulting overall in shorter rendering times. In order to validate and demonstrate the effectiveness of our operator, we render antialiased photorealistic images against ground truth. In addition, we provide C++ implementations all along the dissertation to facilitate the reproduction of the presented results. We conclude with a discussion on limitations of our approach, and avenues for a more general multiscale representation for matter.