A Natural Pixel Decomposition for Two-Dimensional Image Reconstruction

Abstract

In two-dimensional image reconstruction from line integrals using maximum likelihood, Bayesian, or minimum variance algorithms, the x-y plane on which the object estimate is defined is decomposed into nonoverlapping regions, or "pixels." This decomposition of an otherwise continuous structure results in significant errors, or model noise, which can exceed the effects of the fundamental measurement noise.