Abstract
An analysis of image reconstruction with one- and two-dimensional convolution methods is presented in an outline of the relationship among the correction functions, the point spread function and the statistical noise. The correction functions are derived which maximize the ratio of one-dimensional signal power to noise power for a given r.m.s. resolution width in a uniform image. The texture of the image noise is expressed by the autocovariance function. For emission images, the variance of noise is expressed by the convolution of the source distribution with the “error kernel” which is determined from the one-dimensional correction function.
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