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Hi,
as announced in the MegaPOV-Thread i've made a small webpage
to show my new radiosity-sampleset. The URL is:
http://www.8ung.at/halcyon/povray/custom-radiosity.html
What do you think?
I'm excited to get your feedback :)
Greetings,
Thies
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oh, i've forgotten to mention that the page is relatively big (about 4 MB)
because of the images.
I'm sorry for that, but i thought for comparisons with such small
differences jpegs destroy the images too much. I hope you understand.
Thies
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Thies Heidecke wrote:
> Hi,
> as announced in the MegaPOV-Thread i've made a small webpage
> to show my new radiosity-sampleset. The URL is:
>
> http://www.8ung.at/halcyon/povray/custom-radiosity.html
>
> What do you think?
> I'm excited to get your feedback :)
That's a regular distribution and this means it is a very bad one for
general purpose. This does not mean it can't lead to better results
under certain circumstances.
In case it isn't immediately clear why a regular distribution is bad -
the lower edge of your sample set for example follows a certain pattern
- this pattern is the most likely cause of artefacts.
--
Christoph Hormann
http://www.tu-bs.de/~y0013390/
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"Christoph Hormann" <chr### [at] gmx de> schrieb im Newsbeitrag
news:4126458a$1@news.povray.org...
> Thies Heidecke wrote:
> > Hi,
> > as announced in the MegaPOV-Thread i've made a small webpage
> > to show my new radiosity-sampleset. The URL is:
> >
> > http://www.8ung.at/halcyon/povray/custom-radiosity.html
> >
> > What do you think?
> > I'm excited to get your feedback :)
>
> That's a regular distribution and this means it is a very bad one for
> general purpose. This does not mean it can't lead to better results
> under certain circumstances.
>
> In case it isn't immediately clear why a regular distribution is bad -
> the lower edge of your sample set for example follows a certain pattern
> - this pattern is the most likely cause of artefacts.
Although one can see the typical spiralling patterns of phyllotaxis it isn't
(considered on a certain level) as regular as it seems. In fact, the pattern
is, because of the golden ratio involved, angle-wise the most irregular
sampling
don't exist with the sunflower-pattern.
Could you show me an example-scene where these kind of artifacts caused by
regular-distribution sampling can be seen?
> Christoph Hormann
Greetings,
Thies
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Thies Heidecke wrote:
> Hi,
> as announced in the MegaPOV-Thread i've made a small webpage
> to show my new radiosity-sampleset. The URL is:
>
> http://www.8ung.at/halcyon/povray/custom-radiosity.html
>
> What do you think?
> I'm excited to get your feedback :)
>
> Greetings,
> Thies
>
>
This is very interesting, Thies! Could you also test with an indoor
scene? How about a room with a small window letting in bright sunlight?
Regards,
--
-------------------------
George Pantazopoulos
http://www.gammaburst.net
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"George Pantazopoulos" <geo### [at] seemysignature> schrieb im Newsbeitrag
news:41275df6$1@news.povray.org...
> Thies Heidecke wrote:
> > Hi,
> > as announced in the MegaPOV-Thread i've made a small webpage
> > to show my new radiosity-sampleset. The URL is:
> >
> > http://www.8ung.at/halcyon/povray/custom-radiosity.html
> >
> > What do you think?
> > I'm excited to get your feedback :)
> >
>
> This is very interesting, Thies! Could you also test with an indoor
> scene? How about a room with a small window letting in bright sunlight?
Hi,
thanks for your interest!
A third scene is underway at the moment. I'm currently rendering the
reference-image with count 6400, that will take a few hours, then i'll
make a series of images to compare like in the other scenes.
The scene consists of a simple closed room which is divided by a row
of columns and a strong lightsource on one side of the room and the
camera on the other side.
I'm also considering making images with the halton-sequence-set to
compare. I'll let you know when i've uploaded the new scene.
> Regards,
> George Pantazopoulos
Greetings,
Thies
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I actually tried this golden ratio approach two years ago iirc and our brain
is very good at detecting patterns and regular artifacts, so unfortunately
it doesn't work so good for low sample amounts. But for very high sample
counts I think it's ok though.
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"Eli" <eli### [at] jehoelnet> schrieb im Newsbeitrag
news:41276939@news.povray.org...
> I actually tried this golden ratio approach two years ago iirc and our
brain
> is very good at detecting patterns and regular artifacts, so unfortunately
> it doesn't work so good for low sample amounts. But for very high sample
> counts I think it's ok though.
Perhaps you and christoph are right about the regular-pattern-thing. The
reason why i'm so sceptical until now is, that i haven't seen a scene yet
where my approach looks worse than the internal sampleset. Although the
reason for that could be that my scenes don't show that artifacts off
good enough (i think the indoor-scene will give more possibilities to
compare). But i must say that especially at low count-values i found the
golden-ratio approach not looking very regular.
Greetings,
Thies
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The Cornell box is a good test scene.
I think a sample set should work at low sample counts.
Maybe jittering the set in order to get rid of the visible patterns should
help.
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"Eli" <eli### [at] jehoelnet> schrieb im Newsbeitrag
news:4128b0aa$1@news.povray.org...
> The Cornell box is a good test scene.
I will first finish the renderings based on my current indoor-scene
because i've already rendered a few images and hours.
> I think a sample set should work at low sample counts.
What do you mean? I don't understand.
If you refer to my last sentence in the last post, i wanted
to say that especially at low sample-numbers it is hard to
detect a pattern in the golden-ratio approach so i think it's
quite good at low sample-values
> Maybe jittering the set in order to get rid of the visible patterns should
> help.
That's a good idea which i'm already trying at the moment. Perhaps this
is the most flexible solution. Combining the good distribution of the
goldenratio-method with the natural artifact-avoiding look of random
placement of samples.
Greetings,
Thies
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