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A signal-processing framework for reflection
A Signal-Processing Framework for Reflection
RAVI RAMAMOORTHI
Columbia University
and
PAT HANRAHAN
Stanford University
We present a signal-processing framework for analyzing the reflected light field from a homogeneous convex curved surface
under distant illumination. This analysis is of theoretical interest in both graphics and vision and is also of practical importance
in many computer graphics problems—for instance, in determining lighting distributions and bidirectional reflectance distribu-
tion functions (BRDFs), in rendering with environment maps, and in image-based rendering. It is well known that under our
assumptions, the reflection operator behaves qualitatively like a convolution. In this paper, we formalize these notions, showing
that the reflected light field can be thought of in a precise quantitative way as obtained by convolving the lighting and BRDF, i.e.
by filtering the incident illumination using the BRDF. Mathematically, we are able to express the frequency-space coefficients of
the reflected light field as a product of the spherical harmonic coefficients of the illumination and the BRDF. These results are of
practical importance in determining the well-posedness and conditioning of problems in inverse rendering—estimation of BRDF
and lighting parameters from real photographs. Furthermore, we are able to derive analytic formulae for the spherical harmonic
coefficients of many common BRDF and lighting models. From this formal analysis, we are able to determine precise conditions
under which estimation of BRDFs and lighting distributions are well posed and well-conditioned. Our mathematical analysis
also has implications for forward rendering—especially the efficient rendering of objects under complex lighting conditions spec-
ified by environment maps. The results, especially the analytic formulae derived for Lambertian surfaces, are also relevant in
computer vision in the areas of recognition, photometric stereo and structure from motion.
Categ
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