137 lines
6.2 KiB
TeX
137 lines
6.2 KiB
TeX
\newpage
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\subsection{Reconstruction filters}
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\label{sec:rfilters}
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Image reconstruction filters are responsible for converting a series of radiance samples generated
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jointly by the \emph{sampler} and \emph{integrator} into the final output image that will be written
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to disk at the end of a rendering process.
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This section gives a brief overview of the reconstruction filters that are available in Mitsuba.
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There is no universally superior filter, and the final choice depends on a trade-off between
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sharpness, ringing, and aliasing, and computational efficiency.
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Desireable properties of a reconstruction filter are that it sharply captures all of the details that
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are displayable at the requested image resolution, while avoiding aliasing and ringing. Aliasing is
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the incorrect leakage of high-frequency into low-frequency detail, and ringing denotes oscillation artifacts
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near discontinuities, such as a light-shadow transiton.
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\begin{description}
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\item[Box filter (\code{box}):]
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the fastest, but also about the worst possible
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reconstruction filter, since it is extremely prone to aliasing.
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It is included mainly for completeness, though some rare situations
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may warrant its use.
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\item[Tent filter (\code{tent}):]
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Simple tent, or triangle filter. This reconstruction filter never
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suffers from ringing and usually causes less aliasing than a naive
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box filter. When rendering scenes with sharp brightness discontinuities,
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this may be useful; otherwise, negative-lobed filters will be preferable
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(e.g. Mitchell-Netravali or Lanczos Sinc)
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\item[Gaussian filter (\code{gaussian}):]
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this is a windowed Gaussian filter with configurable standard deviation.
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It produces pleasing results and never suffers from ringing, but may
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occasionally introduce too much blurring.
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When no reconstruction filter is explicitly requested, this is the default
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choice in Mitsuba. Takes a standard deviation parameter (\code{stddev})
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which is set to 0.5 pixels by default.
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\item[Mitchell-Netravali filter (\code{mitchell}):]
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Separable cubic spline reconstruction filter by Mitchell and Netravali
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\cite{Mitchell:1988:Reconstruction}
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This is often a good compromise between sharpness and ringing.
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The plugin has two \code{float}-valued parameters named \texttt{B} and \texttt{C} that
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correspond to the two parameters in the original research paper. By default, these
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are set to the recommended value of $1/3$, but can be tweaked if desired.
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\item[Catmull-Rom filter (\code{catmullrom}):]
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This is a special version of the Mitchell-Netravali filter that has the
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constants \texttt{B} and \texttt{C} adjusted to produce higher sharpness at the
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cost of increased susceptibility to ringing.
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\item[Lanczos Sinc filter (\code{lanczos}):]
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This is a windowed version of the theoretically optimal low-pass filter.
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It is generally one of the best available filters in terms of producing sharp
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high-quality output. Its main disadvantage is that it produces strong ringing around
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discontinuities, which can become a serious problem when rendering bright objects
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with sharp edges (for instance, a directly visible light source will have black
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fringing artifacts around it).
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This is also the computationally slowest reconstruction filter.
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This plugin has an \code{integer}-valued parameter named \code{lobes}, that
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sets the desired number of filter side-lobes. The higher, the closer
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the filter will approximate an optimal low-pass filter, but this also
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increases the susceptibility to ringing. Values of 2 or 3 are common (3 is the default).
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\end{description}
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The next section contains a series of comparisons between reconstruction filters. In the first
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case, a very high-resolution input image (corresponding to a hypothetical radiance field
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incident at the camera) is reconstructed at low resolutions.
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\newpage
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\subsubsection{Reconstruction filter comparison 1: frequency attenuation and aliasing}
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\vspace{-2mm}
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Here, a high frequency function is reconstructed at low resolutions. A good filter
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(e.g. Lanczos Sinc) will capture all oscillations that are representable at the desired
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resolution and attenuate the remainder to a uniform gray. The filters are ordered by their
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approximate level of success at this benchmark.
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\renderings{
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\subfloat[A high resolution input image whose frequency decreases
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towards the borders. If you are looking at this on a computer, you may
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have to zoom in.]{\fbox{\includegraphics[width=0.43\textwidth]{images/rfilter_sines_input}}}
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\hfill
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}
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\vspace{-4mm}
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\renderings{
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\medrendering{Box filter}{rfilter_sines_box}
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\medrendering{Tent filter}{rfilter_sines_tent}
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\medrendering{Gaussian filter}{rfilter_sines_gaussian}
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}
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\vspace{-4mm}
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\renderings{
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\setcounter{subfigure}{3}
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\medrendering{Mitchell-Netravali filter}{rfilter_sines_mitchell}
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\medrendering{Catmull-Rom filter}{rfilter_sines_catmullrom}
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\medrendering{Lanczos Sinc filter}{rfilter_sines_lanczos}
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}
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\newpage
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\subsubsection{Reconstruction filter comparison 2: ringing}
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This comparison showcases the ringing artifacts that can occur when the rendered
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image contains extreme and discontinuous brightness transitions. The
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Mitchell-Netravali, Catmull-Rom, and Lanczos Sinc filters are affected by this problem.
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Note the black fringing around the light source in the cropped Cornell box renderings below.
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\renderings{
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\rendering{Box filter}{rfilter_cbox_box}
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\rendering{Tent filter}{rfilter_cbox_tent}
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}
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\vspace{-4mm}
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\renderings{
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\setcounter{subfigure}{2}
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\rendering{Gaussian filter}{rfilter_cbox_gaussian}
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\rendering{Mitchell-Netravali filter}{rfilter_cbox_mitchell}
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}
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\vspace{-4mm}
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\renderings{
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\setcounter{subfigure}{4}
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\rendering{Catmull-Rom filter}{rfilter_cbox_catmullrom}
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\rendering{Lanczos Sinc filter}{rfilter_cbox_lanczos}
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}
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\subsubsection{Specifying a reconstruction filter}
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To specify a reconstruction filter, it must be instantiated inside
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the sensor's film. Below is an example:
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\begin{xml}
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<scene version=$\MtsVer$>
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<!-- ... scene contents ... -->
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<sensor type="... sensor type ...">
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<!-- ... sensor parameters ... -->
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<film type="... film type ...">
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<!-- ... film parameters ... -->
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<!-- Instantiate a Lanczos Sinc filter with two lobes -->
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<rfilter type="lanczos">
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<integer name="lobes" value="2"/>
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</rfilter>
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</film>
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</sensor>
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</scene>
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\end{xml}
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