Iterated function system

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Sierpinski triangle created using IFS (colored to illustrate self-similar structure) Sierpinski1.png
Sierpinski triangle created using IFS (colored to illustrate self-similar structure)
Colored IFS designed using Apophysis software and rendered by the Electric Sheep. Chris Ursitti fractal 0000.png
Colored IFS designed using Apophysis software and rendered by the Electric Sheep.

In mathematics, iterated function systems (IFSs) are a method of constructing fractals; the resulting fractals are often self-similar. IFS fractals are more related to set theory than fractal geometry. [1] They were introduced in 1981.

Contents

IFS fractals, as they are normally called, can be of any number of dimensions, but are commonly computed and drawn in 2D. The fractal is made up of the union of several copies of itself, each copy being transformed by a function (hence "function system"). The canonical example is the Sierpiński triangle. The functions are normally contractive, which means they bring points closer together and make shapes smaller. Hence, the shape of an IFS fractal is made up of several possibly-overlapping smaller copies of itself, each of which is also made up of copies of itself, ad infinitum. This is the source of its self-similar fractal nature.

Definition

Formally, an iterated function system is a finite set of contraction mappings on a complete metric space. [2] Symbolically,

is an iterated function system if each is a contraction on the complete metric space .

Properties

Construction of an IFS by the chaos game (animated) Chaosgame.gif
Construction of an IFS by the chaos game (animated)
IFS being made with two functions. Ifs-construction.png
IFS being made with two functions.

Hutchinson showed that, for the metric space , or more generally, for a complete metric space , such a system of functions has a unique nonempty compact (closed and bounded) fixed set S. [3] One way of constructing a fixed set is to start with an initial nonempty closed and bounded set S0 and iterate the actions of the fi, taking Sn+1 to be the union of the images of Sn under the fi; then taking S to be the closure of the limit . Symbolically, the unique fixed (nonempty compact) set has the property

The set S is thus the fixed set of the Hutchinson operator defined for via

The existence and uniqueness of S is a consequence of the contraction mapping principle, as is the fact that

for any nonempty compact set in . (For contractive IFS this convergence takes place even for any nonempty closed bounded set ). Random elements arbitrarily close to S may be obtained by the "chaos game," described below.

Recently it was shown that the IFSs of non-contractive type (i.e. composed of maps that are not contractions with respect to any topologically equivalent metric in X) can yield attractors. These arise naturally in projective spaces, though classical irrational rotation on the circle can be adapted too. [4]

The collection of functions generates a monoid under composition. If there are only two such functions, the monoid can be visualized as a binary tree, where, at each node of the tree, one may compose with the one or the other function (i.e. take the left or the right branch). In general, if there are k functions, then one may visualize the monoid as a full k-ary tree, also known as a Cayley tree.

Constructions

Barnsley's fern, an early IFS Fractal fern explained.png
Barnsley's fern, an early IFS
Menger sponge, a 3-Dimensional IFS. Menger sponge (IFS).jpg
Menger sponge, a 3-Dimensional IFS.
IFS "tree" constructed with non-linear function Julia Coupe d'arbre.png
IFS "tree" constructed with non-linear function Julia
HERBO avecTige.png

Sometimes each function is required to be a linear, or more generally an affine, transformation, and hence represented by a matrix. However, IFSs may also be built from non-linear functions, including projective transformations and Möbius transformations. The Fractal flame is an example of an IFS with nonlinear functions.

The most common algorithm to compute IFS fractals is called the "chaos game". It consists of picking a random point in the plane, then iteratively applying one of the functions chosen at random from the function system to transform the point to get a next point. An alternative algorithm is to generate each possible sequence of functions up to a given maximum length, and then to plot the results of applying each of these sequences of functions to an initial point or shape.

Each of these algorithms provides a global construction which generates points distributed across the whole fractal. If a small area of the fractal is being drawn, many of these points will fall outside of the screen boundaries. This makes zooming into an IFS construction drawn in this manner impractical.

Although the theory of IFS requires each function to be contractive, in practice software that implements IFS only require that the whole system be contractive on average. [5]

Partitioned iterated function systems

PIFS (partitioned iterated function systems), also called local iterated function systems, [6] give surprisingly good image compression, even for photographs that don't seem to have the kinds of self-similar structure shown by simple IFS fractals. [7]

The inverse problem

Very fast algorithms exist to generate an image from a set of IFS or PIFS parameters. It is faster and requires much less storage space to store a description of how it was created, transmit that description to a destination device, and regenerate that image anew on the destination device, than to store and transmit the color of each pixel in the image. [6]

The inverse problem is more difficult: given some original arbitrary digital image such as a digital photograph, try to find a set of IFS parameters which, when evaluated by iteration, produces another image visually similar to the original. In 1989, Arnaud Jacquin presented a solution to a restricted form of the inverse problem using only PIFS; the general form of the inverse problem remains unsolved. [8] [9] [6]

As of 1995, all fractal compression software is based on Jacquin's approach. [9]

Examples

The diagram shows the construction on an IFS from two affine functions. The functions are represented by their effect on the bi-unit square (the function transforms the outlined square into the shaded square). The combination of the two functions forms the Hutchinson operator. Three iterations of the operator are shown, and then the final image is of the fixed point, the final fractal.

Early examples of fractals which may be generated by an IFS include the Cantor set, first described in 1884; and de Rham curves, a type of self-similar curve described by Georges de Rham in 1957.

History

IFSs were conceived in their present form by John E. Hutchinson in 1981 [3] and popularized by Michael Barnsley's book Fractals Everywhere.

IFSs provide models for certain plants, leaves, and ferns, by virtue of the self-similarity which often occurs in branching structures in nature.

Michael Barnsley et al. [10]

See also

Notes

  1. Zobrist, George Winston; Chaman Sabharwal (1992). Progress in Computer Graphics: Volume 1. Intellect Books. p. 135. ISBN   9780893916510 . Retrieved 7 May 2017.
  2. Michael Barnsley (1988). Fractals Everywhere, p.82. Academic Press, Inc. ISBN   9780120790623.
  3. 1 2 Hutchinson, John E. (1981). "Fractals and self similarity" (PDF). Indiana Univ. Math. J. 30 (5): 713–747. doi: 10.1512/iumj.1981.30.30055 .
  4. M. Barnsley, A. Vince, The Chaos Game on a General Iterated Function System
  5. Draves, Scott; Erik Reckase (July 2007). "The Fractal Flame Algorithm" (PDF). Archived from the original (PDF) on 2008-05-09. Retrieved 2008-07-17.
  6. 1 2 3 Bruno Lacroix. "Fractal Image Compression". 1998.
  7. Fischer, Yuval (1992-08-12). Przemyslaw Prusinkiewicz (ed.). SIGGRAPH'92 course notes - Fractal Image Compression (PDF). SIGGRAPH. Vol. Fractals - From Folk Art to Hyperreality. ACM SIGGRAPH. Archived from the original (PDF) on 2017-09-12. Retrieved 2017-06-30.
  8. Dietmar Saupe, Raouf Hamzaoui. "A Review of the Fractal Image Compression Literature".
  9. 1 2 John Kominek. "Algorithm for Fast Fractal Image Compression". doi : 10.1117/12.206368.
  10. Michael Barnsley, et al., "V-variable fractals and superfractals" (PDF). (2.22 MB)

Related Research Articles

In mathematics, the Cantor set is a set of points lying on a single line segment that has a number of unintuitive properties. It was discovered in 1874 by Henry John Stephen Smith and mentioned by German mathematician Georg Cantor in 1883.

<span class="mw-page-title-main">Hausdorff dimension</span> Invariant measure of fractal dimension

In mathematics, Hausdorff dimension is a measure of roughness, or more specifically, fractal dimension, that was introduced in 1918 by mathematician Felix Hausdorff. For instance, the Hausdorff dimension of a single point is zero, of a line segment is 1, of a square is 2, and of a cube is 3. That is, for sets of points that define a smooth shape or a shape that has a small number of corners—the shapes of traditional geometry and science—the Hausdorff dimension is an integer agreeing with the usual sense of dimension, also known as the topological dimension. However, formulas have also been developed that allow calculation of the dimension of other less simple objects, where, solely on the basis of their properties of scaling and self-similarity, one is led to the conclusion that particular objects—including fractals—have non-integer Hausdorff dimensions. Because of the significant technical advances made by Abram Samoilovitch Besicovitch allowing computation of dimensions for highly irregular or "rough" sets, this dimension is also commonly referred to as the Hausdorff–Besicovitch dimension.

<span class="mw-page-title-main">Monoid</span> Algebraic structure with an associative operation and an identity element

In abstract algebra, a branch of mathematics, a monoid is a set equipped with an associative binary operation and an identity element. For example, the nonnegative integers with addition form a monoid, the identity element being 0.

<span class="mw-page-title-main">Self-similarity</span> Whole of an object being mathematically similar to part of itself

In mathematics, a self-similar object is exactly or approximately similar to a part of itself. Many objects in the real world, such as coastlines, are statistically self-similar: parts of them show the same statistical properties at many scales. Self-similarity is a typical property of fractals. Scale invariance is an exact form of self-similarity where at any magnification there is a smaller piece of the object that is similar to the whole. For instance, a side of the Koch snowflake is both symmetrical and scale-invariant; it can be continually magnified 3x without changing shape. The non-trivial similarity evident in fractals is distinguished by their fine structure, or detail on arbitrarily small scales. As a counterexample, whereas any portion of a straight line may resemble the whole, further detail is not revealed.

<span class="mw-page-title-main">Julia set</span> Fractal sets in complex dynamics of mathematics

In the context of complex dynamics, a branch of mathematics, the Julia set and the Fatou set are two complementary sets defined from a function. Informally, the Fatou set of the function consists of values with the property that all nearby values behave similarly under repeated iteration of the function, and the Julia set consists of values such that an arbitrarily small perturbation can cause drastic changes in the sequence of iterated function values. Thus the behavior of the function on the Fatou set is "regular", while on the Julia set its behavior is "chaotic".

<span class="mw-page-title-main">Fractal compression</span> Compression method for digital images

Fractal compression is a lossy compression method for digital images, based on fractals. The method is best suited for textures and natural images, relying on the fact that parts of an image often resemble other parts of the same image. Fractal algorithms convert these parts into mathematical data called "fractal codes" which are used to recreate the encoded image.

<span class="mw-page-title-main">Dragon curve</span> Fractal constructible with L-systems

A dragon curve is any member of a family of self-similar fractal curves, which can be approximated by recursive methods such as Lindenmayer systems. The dragon curve is probably most commonly thought of as the shape that is generated from repeatedly folding a strip of paper in half, although there are other curves that are called dragon curves that are generated differently.

<span class="mw-page-title-main">Fractal flame</span>

Fractal flames are 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 and translated into the Apophysis fractal flame editor.

In mathematics, the Lévy C curve is a self-similar fractal curve that was first described and whose differentiability properties were analysed by Ernesto Cesàro in 1906 and Georg Faber in 1910, but now bears the name of French mathematician Paul Lévy, who was the first to describe its self-similarity properties as well as to provide a geometrical construction showing it as a representative curve in the same class as the Koch curve. It is a special case of a period-doubling curve, a de Rham curve.

<span class="mw-page-title-main">Chaos game</span> Method of creating a fractal, using a polygon and an initial point selected at random inside it

In mathematics, the term chaos game originally referred to a method of creating a fractal, using a polygon and an initial point selected at random inside it. The fractal is created by iteratively creating a sequence of points, starting with the initial random point, in which each point in the sequence is a given fraction of the distance between the previous point and one of the vertices of the polygon; the vertex is chosen at random in each iteration. Repeating this iterative process a large number of times, selecting the vertex at random on each iteration, and throwing out the first few points in the sequence, will often produce a fractal shape. Using a regular triangle and the factor 1/2 will result in the Sierpinski triangle, while creating the proper arrangement with four points and a factor 1/2 will create a display of a "Sierpinski Tetrahedron", the three-dimensional analogue of the Sierpinski triangle. As the number of points is increased to a number N, the arrangement forms a corresponding (N-1)-dimensional Sierpinski Simplex.

<span class="mw-page-title-main">Newton fractal</span> Boundary set in the complex plane

The Newton fractal is a boundary set in the complex plane which is characterized by Newton's method applied to a fixed polynomial p(z) ∈ [z] or transcendental function. It is the Julia set of the meromorphic function zzp(z)/p′(z) which is given by Newton's method. When there are no attractive cycles (of order greater than 1), it divides the complex plane into regions Gk, each of which is associated with a root ζk of the polynomial, k = 1, …, deg(p). In this way the Newton fractal is similar to the Mandelbrot set, and like other fractals it exhibits an intricate appearance arising from a simple description. It is relevant to numerical analysis because it shows that (outside the region of quadratic convergence) the Newton method can be very sensitive to its choice of start point.

In mathematics, a de Rham curve is a continuous fractal curve obtained as the image of the Cantor space, or, equivalently, from the base-two expansion of the real numbers in the unit interval. Many well-known fractal curves, including the Cantor function, Cesàro–Faber curve, Minkowski's question mark function, blancmange curve, and the Koch curve are all examples of de Rham curves. The general form of the curve was first described by Georges de Rham in 1957.

In mathematics, an iterated binary operation is an extension of a binary operation on a set S to a function on finite sequences of elements of S through repeated application. Common examples include the extension of the addition operation to the summation operation, and the extension of the multiplication operation to the product operation. Other operations, e.g., the set-theoretic operations union and intersection, are also often iterated, but the iterations are not given separate names. In print, summation and product are represented by special symbols; but other iterated operators often are denoted by larger variants of the symbol for the ordinary binary operator. Thus, the iterations of the four operations mentioned above are denoted

In numerical analysis, fixed-point iteration is a method of computing fixed points of a function.

<span class="mw-page-title-main">Hutchinson metric</span>

In mathematics, the Hutchinson metric otherwise known as Kantorovich metric is a function which measures "the discrepancy between two images for use in fractal image processing" and "can also be applied to describe the similarity between DNA sequences expressed as real or complex genomic signals".

In mathematics, in the study of fractals, a Hutchinson operator is the collective action of a set of contractions, called an iterated function system. The iteration of the operator converges to a unique attractor, which is the often self-similar fixed set of the operator.

<span class="mw-page-title-main">Fractal-generating software</span>

Fractal-generating software is any type of graphics software that generates images of fractals. There are many fractal generating programs available, both free and commercial. Mobile apps are available to play or tinker with fractals. Some programmers create fractal software for themselves because of the novelty and because of the challenge in understanding the related mathematics. The generation of fractals has led to some very large problems for pure mathematics.

In mathematics, the collage theorem characterises an iterated function system whose attractor is close, relative to the Hausdorff metric, to a given set. The IFS described is composed of contractions whose images, as a collage or union when mapping the given set, are arbitrarily close to the given set. It is typically used in fractal compression.

<span class="mw-page-title-main">Barnsley fern</span> Fractal which resembles a plant

The Barnsley fern is a fractal named after the British mathematician Michael Barnsley who first described it in his book Fractals Everywhere. He made it to resemble the black spleenwort, Asplenium adiantum-nigrum.

<span class="mw-page-title-main">Open set condition</span> Condition for fractals in math

In fractal geometry, the open set condition (OSC) is a commonly imposed condition on self-similar fractals. In some sense, the condition imposes restrictions on the overlap in a fractal construction. Specifically, given an iterated function system of contractive mappings , the open set condition requires that there exists a nonempty, open set V satisfying two conditions:

  1. The sets are pairwise disjoint.

References