19 May 1992 Data interpolation techniques applied to image modeling
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Abstract
Image models are a fundamental component of mathematically-founded image processing algorithm. Nonlinear, adaptive, local image models have a significant similarity with methods for interpolating data in many-dimensional spaces. The applicability of these methods will be demonstrated by mathematical analysis and experimental application to natural color scenes. In particular, a modification of the method of radial basis functions will be evaluated and various techniques for determining radial basis centers will be compared: random choice, k-means optimal, and two iterative constructive techniques.
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David R. Cok, David R. Cok, "Data interpolation techniques applied to image modeling", Proc. SPIE 1657, Image Processing Algorithms and Techniques III, (19 May 1992); doi: 10.1117/12.58354; https://doi.org/10.1117/12.58354
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