Electric Asturias: Fractals is a music studio album recording by ASTURIAS (Neo-Prog/Progressive Rock) released in 2011 on cd, lp / vinyl and/or cassette. Fractal flames is a member of the iterated function system class of fractals created by Scott Draves in 1992. Draves' open-source code was later ported into Adobe After Effects graphics software 3 and translated into the Apophysis fractal flame editor.
![]()
(Redirected from Flame fractals)
A fractal flame created by the Electric Sheep.
Fractal flame created in Apophysis.
Fractal flames is a member of the iterated function system class[1] of fractals created by Scott Draves in 1992.[2] Draves' open-source code was later ported into Adobe After Effects graphics software[3] and translated into the Apophysis fractal flame editor.[2]
Fractal flames differ from ordinary iterated function systems in three ways:
![]()
The tone mapping and coloring are designed to display as much of the detail of the fractal as possible, which generally results in a more aesthetically pleasing image.
Algorithm[edit]
The algorithm consists of two steps: creating a histogram and then rendering the histogram.
Creating the histogram[edit]
First one iterates a set of functions, starting from a randomly chosen point P = (P.x,P.y,P.c), where the third coordinate indicates the current color of the point.
In each iteration, choose one of the functions above where the probability that Fj is chosen is pj. Then one computes the next iteration of P by applying Fj on (P.x,P.y).
Each individual function has the following form:
where the parameter wk is called the weight of the variationVk. Draves suggests[4] that all wk{displaystyle w_{k}}:s are non-negative and sum to one, but implementations such as Apophysis do not impose that restriction.
The functions Vk are a set of predefined functions. A few examples[4] are
The color P.c of the point is blended with the color associated with the latest applied function Fj:
After each iteration, one updates the histogram at the point corresponding to (P.x,P.y). This is done as follows:
The colors in the image will therefore reflect what functions were used to get to that part of the image.
Rendering an image[edit]
To increase the quality of the image, one can use supersampling to decrease the noise. This involves creating a histogram larger than the image so each pixel has multiple data points to pull from.
For example, creating a histogram with 300Ã300 cells in order to draw a 100Ã100 px image. Each pixel would use a 3Ã3 group of histogram buckets to calculate its value.
For each pixel (x,y) in the final image, do the following computations:
The algorithm above uses gamma correction to make the colors appear brighter. This is implemented in for example the Apophysis software.
To increase the quality even more, one can use gamma correction on each individual color channel, but this is a very heavy computation, since the log function is slow.
A simplified algorithm would be to let the brightness be linearly dependent on the frequency:
but this would make some parts of the fractal lose detail, which is undesirable.[4]
Density Estimation[edit]
A demonstration of Density Estimation. In the above half, you can see the noise and individual samples. On the below half, rendered with Density Estimation, the noise is smoothed out without destroying the sharp edges.
The flame algorithm is like a Monte Carlo simulation, with the flame quality directly proportional to the number of iterations of the simulation. The noise that results from this stochastic sampling can be reduced by blurring the image, to get a smoother result in less time. One does not however want to lose resolution in the parts of the image that receive many samples and so have little noise.
This problem can be solved with adaptive density estimation to increase image quality while keeping render times to a minimum. FLAM3 uses a simplification of the methods presented in *Adaptive Filtering for Progressive Monte Carlo Image Rendering*, a paper presented at WSCG 2000 by Frank Suykens and Yves D. Willems. The idea is to vary the width of the filter inversely proportional to the number of samples available.
As a result, areas with few samples and lots of noise get blurred and smoothed, but areas with lots of samples and low noise are left unaffected. See https://github.com/scottdraves/flam3/wiki/Density-Estimation.
Not all Flame implementations use density estimation.
See also[edit]
References[edit]
Retrieved from 'https://en.wikipedia.org/w/index.php?title=Fractal_flame&oldid=916824431'
Fractal flame created in.Fractal flames is a member of the class of created by in 1992. Draves' open-source code was later ported into graphics software and translated into the fractal flame editor.Fractal flames differ from ordinary iterated function systems in three ways:. functions are in addition to. Log-density display instead of linear or binary (a form of ). Color by structure (i.e.
By the recursive path taken) instead of monochrome or by density.The tone mapping and coloring are designed to display as much of the detail of the fractal as possible, which generally results in a more aesthetically pleasing image. Histogram x y FREQUENCY := histogram x y FREQUENCY + 1 histogram x y COLOR := ( histogram x y COLOR + P.
C ) / 2The colors in the image will therefore reflect what functions were used to get to that part of the image.Rendering an image To increase the quality of the image, one can use to decrease the noise. This involves creating a histogram larger than the image so each pixel has multiple data points to pull from.For example, creating a histogram with 300Ã300 cells in order to draw a 100Ã100 px image. Each pixel would use a 3Ã3 group of histogram buckets to calculate its value.For each pixel (x,y) in the final image, do the following computations. Frequencyavg x y := averageofhistogramcellsfrequency ( x, y ); coloravg x y := averageofhistogramcellscolor ( x, y ); alpha x y := log ( frequencyavg x y ) / log ( frequencymax ); //frequencymax is the maximal number of iterations that hit a cell in the histogram. Finalpixelcolor x y := coloravg x y. alpha x y ^ ( 1 / gamma ); //gamma is a value greater than 1.The algorithm above uses to make the colors appear brighter.
This is implemented in for example the Apophysis software.To increase the quality even more, one can use gamma correction on each individual color channel, but this is a very heavy computation, since the log function is slow.A simplified algorithm would be to let the brightness be linearly dependent on the frequency. A demonstration of Density Estimation.
In the above half, you can see the noise and individual samples. On the below half, rendered with Density Estimation, the noise is smoothed out without destroying the sharp edges.The flame algorithm is like a, with the flame quality directly proportional to the number of iterations of the simulation. The noise that results from this stochastic sampling can be reduced by the image, to get a smoother result in less time. One does not however want to lose resolution in the parts of the image that receive many samples and so have little noise.This problem can be solved with adaptive to increase image quality while keeping render times to a minimum.
FLAM3 uses a simplification of the methods presented in.Adaptive Filtering for Progressive Monte Carlo Image Rendering., a paper presented at 2000 by Frank Suykens and Yves D. The idea is to vary the width of the filter to the number of samples available.As a result, areas with few samples and lots of noise get blurred and smoothed, but areas with lots of samples and low noise are left unaffected. See.Not all Flame implementations use density estimation.See also., an open source fractal flame editor for Microsoft Windows., a commercial fractal editor which supports flam3, Apophysis and further generalizations., a multi-platform, open-source fractal flame editor written in Java., a screen saver created by the inventor of fractal flames which renders and displays them with., a, multi OS program that can generate fractal flames., part of KPT 5, and one of three fractal apps in the KPT 5 collection. KPT 5 is a plugin for Photoshop, Photo-Paint, PhotoImpact, and other raster based graphics editors.References.
![]() Comments are closed.
|
AuthorWrite something about yourself. No need to be fancy, just an overview. Archives
March 2023
Categories |