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Proceedings Paper

Image Representation By Means Of Two Dimensional Polynomials
Author(s): Michel Kocher
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Paper Abstract

In this paper, two different methods of representing an image using 2-D polynomials will be presented. In the first approach, the image is segmented into adjacent regions using a region growing algorithm. At the completion of this step, the grey level evolution of every region is approximated by a 2-D polynomial using the least square error method. In the second approach, the segmentation and approximation procedures are merged together. This is achieved by representing the matrix's image by a graph where every node is a mapping of a square of n times n pixels and every edge is a measure of similarity between the two nodes it connects. The graph is then iteratively transformed by using an isotropic node merging algorithm. Lastly, the reduced graph is transformed back to a matrix representation giving the final image. The two algorithms will be compared in terms of growing homogeneity, error control and optimality, and their respective results will be presented.

Paper Details

Date Published: 1 May 1986
PDF: 8 pages
Proc. SPIE 0594, Image Coding, (1 May 1986); doi: 10.1117/12.952215
Show Author Affiliations
Michel Kocher, CERAC Institute (Switzerland)


Published in SPIE Proceedings Vol. 0594:
Image Coding
Thomas S. Huang; Murat Kunt, Editor(s)

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