Use this URL to cite or link to this record in EThOS: https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.363150
Title: Jigsaws and faster fractal pictures
Author: Menzies, Lindsey
ISNI:       0000 0001 3394 5746
Awarding Body: University of Glasgow
Current Institution: University of Glasgow
Date of Award: 1997
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Abstract:
Today it is possible to express a wide range of images as attractors of Iterated Function Systems in the plane. An Iterated Function System, or IFS for short, is a finite collection of contractive affine transformations w1, w2,...,wN, while the attractor A is the limit under repeated application of the associated collage map W(E) = UiWi(E) for any compact set E - that is, Wn(E) → A [2, 12, 25, 26]. Since only 6N real numbers, known as the IFS code, are required to store the image, IFS's are now being widely used as a method of image compression [3, 4, 9] - leading to the need for algorithms which produce the attractor A quickly on a computer screen. In this thesis, we study one such algorithm - the Graphical Algorithm, or GA [5] -whose main characteristic is that maps are applied to points only after their coordinates have been rounded to integers. By introducing the concept of jigsaws of maps - where the jigsaw piece of an integer point (u, v) is the set of all integer points (x, y) such that w(x, y) rounds to (u, v) - and studying the properties of such sets, we reduce the time taken to produce an approximation to the attractor by up to a factor of N, making the GA as accurate as the Adaptive Cut Method (ACM) [11, 25, 26], and a frequently faster option than the popular Random Iteration Algorithm (RIA) [1, 2].
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.363150  DOI: Not available
Keywords: Image compression
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