The primary foeus of the applieation of image proeessing to radiography is the problem of segmentation. The general segmentation problem has been attaeked on a broad front [1,2], and thresholding, in partieular, is a popular method [1,[3][4][5][6]. Unfortunately, geometrie unsharpness destroys the erisp edges needed for unambiguous deeisions, and this diffieulty ean be eonsidered a problem in filtering in whieh the objeet is to devise a high-pass (sharpening) filter.This approach has been studied for more than 20 years [7][8][9][10][11][12][13].The inverse filter ean be devised either in the spatial domain or the frequeney domain.Both eases require either a model of the degradation proeess (geometrie unsharpness), or a set of "ideal" image/degraded image pairs from whieh an inverse filter ean be ealeulated by some estimation method (such as least squares).In the ease of radiography with an ineoherent source, a simple model of the imaging proeess leading to a frequeney domain solution ean be developed.The remainder of this paper deseribes a model of the radiographie proeess and the eonsequenees of eertain eonditions and simplifying assumptions. A partieular method of inverse filtering (Wiener filtering) is applied to some digitized radiographs and the results are diseussed.
IMAGING PROCESSThe formation of radiographie images on a plane loeated at z be shown [14] to be a superposition integral of the formwhere u, v, and ware the direetion eosines with respeet to the X-, y-, and z-axes, P(x',y') is the intensity of an isotropie souree at z = 0, ft(x", y" z") is the attenuation eoeffieient along the ray from