1 May 1994 Shape-based interpolation of multidimensional grey-level images
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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.
© (1994) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
George J. Grevera, George J. Grevera, Jayaram K. Udupa, Jayaram K. Udupa, } "Shape-based interpolation of multidimensional grey-level images", Proc. SPIE 2164, Medical Imaging 1994: Image Capture, Formatting, and Display, (1 May 1994); doi: 10.1117/12.174002; https://doi.org/10.1117/12.174002


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