Fast Multiplexed Acquisition of High-dynamic-range Material Appearance

Abstract

There is tremendous demand for digital representations that allow for materials to be re-lit under as wide a range of illumination scenarios as possible. It is therefore desirable to capture the entire dynamic range of a material's appearance. This process can require excessive shutter times for many materials that reflect only small amounts of light for certain lighting and viewing directions, for instance in the presence of low albedo or self-shadowing. The problem is amplified in the case of image-based appearance models such as the bidirectional texture function (BTF), where possibly many thousands of images are required to accurately sample high-frequency details in the angular domain. We propose to capture material BTFs with their dynamic range compressed by multiplexed illumination. We demonstrate that the signal-dependent noise associated with demultiplexing can be mitigated by means of an existing database of low-noise material BTFs. Moreover, we investigate a method to quickly create a suitable database from scratch.