Integral Sampling in Optics

Publisher Website
Google Scholar
Abstract
An image can be sampled by taking as sample values either the image intensity at defined sample points or the image intensity integrated over regularly spaced raster cells. The latter concept, termed integral sampling, is investigated using deterministic and statistic methods. It is proved that the use of integral rather than point sampling results in reduced error due to aliasing when an image is reconstructed from its samples. Filters for optimal reconstruction from samples taken in the presence of noise are described. The special cases of integral sampling of high-pass filtered images and of binary pulse-code modulated images are analysed. Integral sampling can be performed optically; it is shown to be of practical interest for image evaluation (thematic mapping) and for optical spatial regenerative repeaters.