ON OPTIMAL IMAGE DIGITIZATION

L. Nielsen et al. (1984) recently addressed the problem of determining the optimal discretization grid and quantization depth when a given bivariate function f(x, y) has to be described with a predetermined number of bits. This was done under the assumption that the function value range and mean fluctuation rates in the x and y direction are given, and that ideal point sampling with zero-order-hold interpolation is used in reconstructing the image. The author outlines an alternative approach, based on the assumption that f(x, y) is the sample function of a two-dimensional stationary stochastic process with a known covariance function. Standard integral sampling is used to obtain closed form solutions under the assumption that f(x, y) is (the sample of) a homogeneous and separable Markov process.