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Proceedings Paper

Shape-based interpolation of multidimensional grey-level images
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Paper Abstract

In this paper, we present a new approach for the interpolation of grey data of arbitrary dimension that generalizes the shape-based method from binary data to grey data. The basic idea here is to express the given n-dimensional image as a (closed) surface in the (n + 1)- dimensional space, to interpolate the surface based on its shape, and then to collapse the new surface back to the image form. This method is more general and flexible in many respects than other methods. In addition to being able to handle data of arbitrary dimension, it allows intermixing operations on structures and images. The traditional shape-based interpolation method becomes a particular case of this new methodology. Our preliminary observation is that in regions of smooth as well as sharp intensity changes, the new method (in its simplest form) performs better than linear grey-level interpolation. In regions of scattered, fractal-like structures its performance seems to be inferior to the linear method.

Paper Details

Date Published: 1 May 1994
PDF: 8 pages
Proc. SPIE 2164, Medical Imaging 1994: Image Capture, Formatting, and Display, (1 May 1994); doi: 10.1117/12.174002
Show Author Affiliations
George J. Grevera, Univ. of Pennsylvania (United States)
Jayaram K. Udupa, Univ. of Pennsylvania (United States)

Published in SPIE Proceedings Vol. 2164:
Medical Imaging 1994: Image Capture, Formatting, and Display
Yongmin Kim, Editor(s)

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