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Representations and uses of light distribution functions Lalonde, Paul
Abstract
At their lowest level, all rendering algorithms depend on models of local illumination to define the interplay of light with the surfaces being rendered. These models depend both on the representations of light scattering at a surface due to reflection and to an equal extent on the representation of light sources and light fields. Both emission and reflection have in common that they describe how light leaves a surface as a function of direction. Reflection also depends on an incident light direction. Emission can depend on the position on the light source. We call the functions representing emission and reflection light distribution functions (LDF's). There are some difficulties to using measured light distribution functions. The data sets are very large - the size of the data grows with the fourth power of the sampling resolution. For example, a bidirectional reflectance distribution function (BRDF) sampled at five degrees angular resolution, which is arguably insufficient to capture highlights and other high frequency effects in the reflection, can easily require one and a half million samples. Once acquired this data requires some form of interpolation to use them. Any compression method used must be efficient, both in space and in the time required to evaluate the function at a point or over a range of points. This dissertation examines a wavelet representation of light distribution functions that addresses these issues. A data structure is presented that allows efficient reconstruction of LDFs for a given set of parameters, making the wavelet representation feasible for rendering tasks. Texture mapping methods that take advantage of our LDF representations are examined, as well as techniques for filtering LDFs, and methods for using wavelet compressed bidirection reflectance distribution functions (BRDFs) and light sources with Monte Carlo path tracing algorithms. The wavelet representation effectively compresses BRDF and emission data while inducing only a small error in the reconstructed signal. The representation can be used to evaluate efficiently some integrals that appear in shading computation which allows fast, accurate computation of local shading. The representation can be used to represent light fields and is used to reconstruct views of environments interactively from a precomputed set of views. The representation of the BRDF also allows the efficient generation of reflected directions for Monte Carlo ray tracing applications. The method can be integrated into many different global illumination algorithms, including ray tracers and wavelet radiosity systems.
Item Metadata
Title |
Representations and uses of light distribution functions
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Creator | |
Publisher |
University of British Columbia
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Date Issued |
1997
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Description |
At their lowest level, all rendering algorithms depend on models of local illumination
to define the interplay of light with the surfaces being rendered. These models
depend both on the representations of light scattering at a surface due to reflection
and to an equal extent on the representation of light sources and light fields.
Both emission and reflection have in common that they describe how light
leaves a surface as a function of direction. Reflection also depends on an incident
light direction. Emission can depend on the position on the light source. We call the
functions representing emission and reflection light distribution functions (LDF's).
There are some difficulties to using measured light distribution functions.
The data sets are very large - the size of the data grows with the fourth power of the
sampling resolution. For example, a bidirectional reflectance distribution function
(BRDF) sampled at five degrees angular resolution, which is arguably insufficient
to capture highlights and other high frequency effects in the reflection, can easily
require one and a half million samples. Once acquired this data requires some form
of interpolation to use them. Any compression method used must be efficient, both
in space and in the time required to evaluate the function at a point or over a range
of points.
This dissertation examines a wavelet representation of light distribution functions that addresses these issues. A data structure is presented that allows efficient
reconstruction of LDFs for a given set of parameters, making the wavelet representation
feasible for rendering tasks. Texture mapping methods that take advantage of
our LDF representations are examined, as well as techniques for filtering LDFs, and
methods for using wavelet compressed bidirection reflectance distribution functions
(BRDFs) and light sources with Monte Carlo path tracing algorithms.
The wavelet representation effectively compresses BRDF and emission data
while inducing only a small error in the reconstructed signal. The representation can
be used to evaluate efficiently some integrals that appear in shading computation
which allows fast, accurate computation of local shading. The representation can
be used to represent light fields and is used to reconstruct views of environments
interactively from a precomputed set of views. The representation of the BRDF
also allows the efficient generation of reflected directions for Monte Carlo ray tracing
applications. The method can be integrated into many different global illumination
algorithms, including ray tracers and wavelet radiosity systems.
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Extent |
9178097 bytes
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Genre | |
Type | |
File Format |
application/pdf
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Language |
eng
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Date Available |
2009-06-02
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Provider |
Vancouver : University of British Columbia Library
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Rights |
For non-commercial purposes only, such as research, private study and education. Additional conditions apply, see Terms of Use https://open.library.ubc.ca/terms_of_use.
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DOI |
10.14288/1.0051446
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URI | |
Degree | |
Program | |
Affiliation | |
Degree Grantor |
University of British Columbia
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Graduation Date |
1998-05
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Campus | |
Scholarly Level |
Graduate
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Aggregated Source Repository |
DSpace
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Item Media
Item Citations and Data
Rights
For non-commercial purposes only, such as research, private study and education. Additional conditions apply, see Terms of Use https://open.library.ubc.ca/terms_of_use.