Open AccessON RANDOM ITERATED FUNCTION SYSTEMS WITH GREYSCALE MAPS
Author(s) -
Matthew Demers,
Herb Kunze,
Davide La Torre
Publication year - 2012
Publication title -
image analysis and stereology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.237
H-Index - 27
eISSN - 1854-5165
pISSN - 1580-3139
DOI - 10.5566/ias.v31.p109-120
Subject(s) - grayscale , iterated function system , iterated function , noise (video) , mathematics , signal (programming language) , image (mathematics) , function (biology) , scale (ratio) , algorithm , random noise , computer science , artificial intelligence , pattern recognition (psychology) , fractal , mathematical analysis , geography , evolutionary biology , biology , programming language , cartography
In the theory of Iterated Function Systems (IFSs) it is known that one can find an IFS with greyscale maps (IFSM) to approximate any target signal or image with arbitrary precision, and a systematic approach for doing so was described. In this paper, we extend these ideas to the framework of random IFSM operators. We consider the situation where one has many noisy observations of a particular target signal and show that the greyscale map parameters for each individual observation inherit the noise distribution of the observation. We provide illustrative examples