documentation updates, continued
Wenzel Jakob
parent
7a81c2ae4c
commit
b36ac39b36
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@ -72,7 +72,7 @@
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leads to <tt>14x(2*14)=392</tt> samples
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</param>
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<param name="quality" readableName="Quality" type="float" default="1">
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Quality setting (\kappa in the [Tabellion et al.] paper).
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Quality setting ("kappa" in the [Tabellion et al.] paper).
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A value of 1 should be adequate in most cases.
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</param>
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<param name="gradients" readableName="Irradiance gradients" type="boolean" default="true">
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@ -196,10 +196,10 @@
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<plugin type="integrator" name="path" readableName="Path tracer"
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show="true" className="MIPathTracer" extends="MonteCarloIntegrator">
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<descr>
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Extended path tracer -- uses multiple importance sampling to combine
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two sampling strategies, namely BSDF and luminaire sampling. This class also
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supports volumetric absorption, but does not attempt to solve the
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full radiative transfer equation (see <tt>volpath</tt> if this is needed).
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This integrator implements a basic path tracer with multiple importance sampling and is a <em>good
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default choice</em> when there is no strong reason to prefer another method.
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It does not account for participating media, such as fog or smoke—see
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the volumetric path tracer if this is needed.
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</descr>
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</plugin>
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@ -395,7 +395,7 @@
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when rendering scenes involving depth-of-field, motion blur, and glossy reflections.</p>
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<p>Note that this integrator ignores the sampler
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configuration---hence, the usual steps of choosing a sample generator and a desired
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configuration—hence, the usual steps of choosing a sample generator and a desired
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number of samples per pixel are not necessary. As with PPM, once started,
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the rendering process continues indefinitely until it is manually stopped.</p>
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</descr>
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@ -437,7 +437,7 @@
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are explicitly represented by surfaces in the scene so that they can be
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intersected by random walks started at emitters.</p>
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<p>Bidirectional path tracing is a relatively "heavy" rendering technique---for
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<p>Bidirectional path tracing is a relatively "heavy" rendering technique—for
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the same number of samples per pixel, it is easily 3-4 times slower than regular
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path tracing. However, it usually makes up for this by producing considerably
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lower-variance radiance estimates (i.e. the output images have less noise).</p>
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@ -586,11 +586,27 @@
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<plugin type="integrator" name="mlt" readableName="Path Space MLT" show="true"
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className="MLT" extends="Integrator">
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<descr>
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Veach-style Metropolis Light Transport implementation with support for
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bidirectional mutations, lens perturbations, caustic perturbations and
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multi-chain perturbations. Several optimizations are also implemented, namely
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separate direct illumination, two-stage MLT, and importance sampling of
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mutation strategies. For details, see the respective parameter descriptions.
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<p>Metropolis Light Transport (MLT) is a seminal rendering technique proposed by Veach and
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Guibas, which applies the Metropolis-Hastings
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algorithm to the path-space formulation of light transport.
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Please refer to the PSSMLT documentation for a general description of MLT-type
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algorithms and a list of caveats that also apply to this plugin.</p>
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<p>Like PSSMLT, this integrator explores the space of light paths,
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searching with preference for those that carry a significant amount of
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energy from an emitter to the sensor. The main difference is that PSSMLT
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does this exploration by piggybacking on another rendering technique and
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"manipulating" the random number stream that drives it, whereas MLT does
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not use such an indirection: it operates directly on the actual light
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paths. </p>
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<p>This means that the algorithm has access to considerably more
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information about the problem to be solved, which allows it to perform a
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directed exploration of certain classes of light paths. The main downside
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is that the implementation is rather complex, which may make it more
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susceptible to unforeseen problems. Mitsuba reproduces the full MLT
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algorithm except for the lens subpath mutation. In addition, the plugin also provides the
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manifold perturbation proposed by Jakob and Marschner.</p>
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</descr>
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<param name="maxDepth" readableName="Maximum depth" type="integer" default="-1">
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Specifies the longest path depth in the generated output image (where <tt>-1</tt>
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@ -598,26 +614,24 @@
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2 will lead to single-bounce (direct-only) illumination, and so on.
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</param>
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<param name="directSamples" readableName="Direct samples" type="integer" default="16">
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When <tt>separateDirect</tt> is set to <tt>true</tt>, this parameter can
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be used to specify the samples per pixel used to render the
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direct component. Should be a power of two (otherwise, it will be
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rounded to the next one). When set to zero or less, the
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direct illumination component will be hidden, which is useful
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for analyzing the component rendered by MLT.
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By default, this plugin renders the direct illumination component
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separately using an optimized direct illumination sampling strategy
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that uses low-discrepancy number sequences for superior performance
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(in other words, it is <em>not</em> rendered by MLT). This
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parameter specifies the number of samples allocated to that method. To
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force MLT to be responsible for the direct illumination
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component as well, set this parameter to <tt>-1</tt>.
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</param>
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<param name="twoStage" readableName="Two-stage MLT" type="boolean" default="false">
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This setting can be very useful to reduce noise in dark regions
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of the image: it activates two-stage MLT, where a nested MLT renderer
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first creates a tiny version of the output image. In a second pass,
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the full version is then rendered, while making use of information
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about the image-space luminance distribution found in the first
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pass. Two-stage MLT is very useful in making the noise characteristics
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more uniform over time image -- specifically, since MLT tends to get
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stuck in very bright regions at the cost of the remainder of the image.
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<param name="twoStage" readableName="Two-stage MLT" type="boolean" default="false">
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Use two-stage MLT? Please see the documentation for details.
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</param>
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<param name="luminanceSamples" readableName="Luminance samples" type="integer" default="100000" importance="1">
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Number of samples used to estimate the total luminance
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received by the camera's sensor.
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MLT-type algorithms create output images that are only
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<em>relative</em> The algorithm can e.g. determine that a certain pixel
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is approximately twice as bright as another one, but the absolute
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scale is unknown. To recover it, this plugin computes
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the average luminance arriving at the sensor by generating a
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number of samples.
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</param>
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<param name="bidirectionalMutation" readableName="Bidirectional mutation" type="boolean" default="true" importance="1">
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Selectively enable/disable the bidirectional mutation
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@ -635,27 +649,34 @@
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Selectively enable/disable the manifold perturbation
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</param>
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<param name="probFactor" readableName="Probability factor" type="float" default="50" importance="1">
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Manifold perturbation: probability factor ("lambda")
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</param>
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<param name="timeout" readableName="Timeout" type="integer" default="0" importance="1">
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If set to a nonzero value, the rendering process will automatically be stopped after this many seconds.
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Probability factor ("lambda") of the manifold perturbation
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</param>
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</plugin>
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<plugin type="integrator" name="erpt" readableName="Energy redistribution path tracing" show="true"
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className="EnergyRedistributionPathTracer" extends="Integrator">
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<descr>
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Energy redistribution path tracing as proposed by Cline et al.
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<p>Energy Redistribution Path Tracing (ERPT) by Cline et al.
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combines Path Tracing with the perturbation strategies of Metropolis Light Transport.</p>
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<p>An initial set of <em>seed paths</em> is generated using a standard bidirectional
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path tracer, and for each one, a MLT-style Markov Chain is subsequently started
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and executed for some number of steps.
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This has the effect of redistributing the energy of the individual samples
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over a larger area, hence the name of this method.</p>
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<p>This plugin shares all the perturbation strategies of the MLT plugin, and
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the same rules for selecting them apply. In contrast to the original
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paper by Cline et al., the Mitsuba implementation uses a bidirectional
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(rather than an unidirectional) bidirectional path tracer to create seed paths.
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Also, since they add bias to the output, this plugin does not use the image
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post-processing filters proposed by the authors.</p>
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</descr>
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<param name="maxDepth" readableName="Maximum depth" type="integer" default="-1">
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Specifies the longest path depth in the generated output image (where <tt>-1</tt>
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corresponds to ∞). A value of 1 will only render directly visible light sources.
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2 will lead to single-bounce (direct-only) illumination, and so on.
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</param>
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<param name="rrDepth" readableName="Russian Roulette starting depth" type="integer" default="5" importance="1">
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Specifies the minimum path depth, after which the implementation will start to use the
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"russian roulette" path termination criterion (set to <tt>-1</tt> to disable).
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</param>
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<param name="numChains" readableName="Average number of chains" type="float" default="1">
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Specifies the number of Markov Chains that, on average, are
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started per pixel
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Specifies the number of mutations to be performed in each Markov Chain
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</param>
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<param name="directSamples" readableName="Direct samples" type="integer" default="16">
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When <tt>separateDirect</tt> is set to <tt>true</tt>, this parameter can
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be used to specify the samples per pixel used to render the
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direct component. Should be a power of two (otherwise, it will be
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rounded to the next one). When set to zero or less, the
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direct illumination component will be hidden, which is useful
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for analyzing the component rendered by MLT.
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By default, this plugin renders the direct illumination component
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separately using an optimized direct illumination sampling strategy
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that uses low-discrepancy number sequences for superior performance
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(in other words, it is <em>not</em> rendered by ERPT). This
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parameter specifies the number of samples allocated to that method. To
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force ERPT to be responsible for the direct illumination
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component as well, set this parameter to <tt>-1</tt>.
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</param>
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<param name="luminanceSamples" readableName="Luminance samples" type="integer" default="15000" importance="1">
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Number of samples used to estimate the average contribution of a
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@ -695,22 +717,13 @@
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Selectively enable/disable the manifold perturbation
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</param>
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<param name="probFactor" readableName="Probability factor" type="float" default="50" importance="1">
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Manifold perturbation: probability factor ("lambda")
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Probability factor ("lambda") of the manifold perturbation
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</param>
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<param name="rrDepth" readableName="Russian Roulette starting depth" type="integer" default="5" importance="1">
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When creating seed paths, this parameter specifies the minimum path depth, after which the
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implementation will start to use the
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"russian roulette" path termination criterion (set to <tt>-1</tt> to disable).
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</param>
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</plugin>
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<plugin type="medium" className="Medium" abstract="true">
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<shortDescr>Base class of all participating media</shortDescr>
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<descr>
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Base class of all participating media -- By default, the parameters are set to
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the skim milk data from "A Practical Model for Subsurface scattering" (Jensen et al.)
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</descr>
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<param name="sigmaS" type="spectrum" default="0.7, 1.22, 1.9">Scattering coefficient</param>
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<param name="sigmaT" type="spectrum" default="0.0014, 0.0025, 0.0142">Absorption coefficient</param>
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<param name="sizeMultiplier" type="float" default="1">Scattering/absorption coefficient multiplier - can be used to convert these to world-space units.</param>
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<child type="phase" count="1">
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Specifies the phase function of the medium. If none is specified,
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the default (<tt>isotropic</tt>) is chosen.
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</child>
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</plugin>
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<plugin type="rfilter" readableName="Box filter" name="box" show="true" className="BoxFilter" extends="ReconstructionFilter">
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