| 摘要 |
An image or other multi-dimensional data set may have its sampling rate changed by determining weighting factors for the values of points in the original (input) data set used to calculate the value of a point in the new (output) data set. The weighting factors are determined using a function, such as a Gaussian function, that takes as input the relative location of the point in the new data set with respect to the locations of surrounding (neighboring) points in the original data set. The values of the points in the original data set are multiplied by the weighting factors, and the resultant products are added (or combined by another function) to give a value of the point in the new data set. In particular, when the input and output data sets are regularly spaced, such as with pixels for computer displays, the locations of the surrounding points and thus their weights repeat periodically. This results in increased efficiency because the surrounding points and their weights need to be determined only for a subset of the output data set.
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