Improving resolution of solid state linear array x-ray detectors

Linear solid-state detectors are nowadays a widespread media in industrial and medical x-ray imaging. The resolution reached with this system has been largely improved in these past years, but is still too poor for some high resolution applications. We first have carried out an optimization of the detector characteristics through a behavioral simulation using a hardware description language. Furthermore, our work concerned the resolution enhancement for this kind of detectors via signal processing. Our approach takes into account the modeled point spread function (PSF) of the system. This modeled PSF is obtained with a new edge technique. The knowledge about the system response is used in a restoration scheme in order to improve the response of the detector to the high frequencies in the digital image. The restoration problem is an ill posed problem ad uses an inverse Wiener filtering. Another intrinsic limitation of solid-state detectors is the spatial sampling step. In order to overcome this problem, we also tested the feasibility of a finer sampling of the acquired image, buy interlacing several slightly shifted acquisitions of the same test object. The restoration applied to this finer sampled signal results in a resolution enhancement that is theoretically impossible to reach with a single detector acquisition. Some experimental results obtained on a variable bar-space pattern phantom are presented. This kind of phantom allows for a precise evaluation of the modulation transfer function on the acquired and processed images. The contribution of the image processing to the restoration enhancement can thus be quantified.