At the outset, it will be noted that the phrase "x-ray attenuation information" is used in its broad sense as relating to numerical values characterizing the x-ray attenuation characteristics of a given material. The linear attenuation coefficient is only one example. Other standardized measures, such as density, can be used, and it is also possible to use an arbitrary scale suited to the particular application.
Inspection systems of the type to which the present invention is directed are intended to produce high accuracy attenuation information on a pixel-by-pixel basis for an object being examined. The information can be displayed as an image or alternatively can be processed in a data processor. For example, a processor may be programmed to examine a pixelized set of attenuation data to locate faults in the object which had created the data set. High accuracy is needed in such systems. In one such example, a system is capable of producing 256 gradations in attenuation coefficient, and the preferable accuracy required is an accuracy within two units of the true attenuation.
In a typical x-ray system, such accuracy is not readily available. First of all, the x-ray beam itself typically has hot spots, and the location of the hot spots can change over time, particularly if the tube is switched on and off. A typical sensor for such a system is the image intensifier, and like the x-ray tube, the image intensifier will have localized areas which are more efficient than others, also creating the effect of "hot spots". Misalignment of the beam with respect to the image intensifier can further add to the inaccuracies. Indeed, even the geometry of the system in which the ray length is not constant causes an inherent inaccuracy; the image intensifier has a convex surface normal to the beam and therefore requires a ray length (from the x-ray source focal spot to the image intensifier) which increases with increasing distance from the center of the image intensifier.
A technique called "image subtraction" can conceptually be utilized to correct for some of these errors. In image subtraction, a reference image intended to include as many of the system errors and inaccuracies as possible, can be subtracted from an image to be processed, with the subtraction intending to remove the inaccuracies, leaving simply the image relating to the sample. Image subtraction to remove errors such as those described above presents a number of difficulties, and is not believed adequate to accomplish the necessary correction.