Re-gridding CT-data using Hermitian polynomial curve interpolation
نویسندگان
چکیده
Introduction Re-gridding of data distributed in a spatially grid to finer or coarser resolution is a fundamental task in the field of data processing. The gridding process requires a re-distribution of the original dataset to a user requested grid according to a distribution function, which can be determined on the basis of the given data by interpolation methods. Commonly used interpolation methods are piecewise linear, cubic or higher order polynomial interpolation functions. However, these interpolation functions can result in unrealistic values for the re-gridded dataset. The gridding-algorithm presented in this work was developed in order to overcome these problems.
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