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The collage theorem describes a constructive technique for approximating sets of points in Euclidean space (typically images) to any degree of precision with the attractor of an iterated function system . It is typically used in fractal compression .
Statement of Theorem
Let
X
{\displaystyle \mathbb {X} }
be a complete metric space . Let
L
∈
H
(
X
)
{\displaystyle L\in {\mathcal {H}}(\mathbb {X} )}
be given, and let
ϵ
≥
0
{\displaystyle \epsilon \geq 0}
be given. Choose an Iterated function system (IFS)
{
X
;
w
1
,
w
2
,
…
w
N
}
{\displaystyle \{\mathbb {X} ;w_{1},w_{2},\dots w_{N}\}}
with contractivity factor
0
≤
s
<
1
{\displaystyle 0\leq s<1}
, so that
h
(
L
,
⋃
n
=
1
N
w
n
(
L
)
)
≤
ϵ
{\displaystyle h\left(L,\bigcup _{n=1}^{N}w_{n}(L)\right)\leq \epsilon }
,
where
h
(
d
)
{\displaystyle h(d)}
is the Hausdorff metric . Then
h
(
L
,
A
)
≤
ϵ
/
(
1
−
s
)
{\displaystyle h(L,A)\leq \epsilon /(1-s)}
where
A
{\displaystyle A}
is the attractor of the IFS. Equivalently,
h
(
L
,
A
)
≤
(
1
−
s
)
−
1
h
(
L
,
∪
n
=
1
N
w
n
(
L
)
)
{\displaystyle h(L,A)\leq (1-s)^{-1}h\left(L,\cup _{n=1}^{N}w_{n}(L)\right)}
for all
L
∈
H
(
X
)
{\displaystyle L\in {\mathcal {H}}(\mathbb {X} )}
References
Barnsley, Michael. (1988). Fractals Everywhere . Academic Press, Inc. ISBN 0-12-079062-9 .
See also
External links