19 May 1992 Data interpolation techniques applied to image modeling
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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.
© (1992) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
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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