Nonstationary filtering of transmission tomograms in high photon counting noise.

The algorithm presented here for nonstationary constrained least-squares filtering deals with the transmission photon counting noise problem in the presence of limited dosages and highly nonhomogeneous fields. This technique consists of a design for a set of nonstationary filters, tuned to local noise autocorrelation functions in the reconstructed image. Estimates of noise properties can be taken from object detection information. The approach yields improvement in the tradeoff between noise levels and resolution of the image by exchanging artifacts for less colored noise, which is more easily overcome by the viewer.