In most application of diagnostic imaging the amount of digitized information (up to 4096 grey levels per pixel) cannot be detected by the human observer as a whole, so that it is common practice to interactively select a suitable intensity window for the display, sometimes with saturation effects. To overcome this problem many different contrast stretching approaches have been proposed, to almost equalize the diagnostic information on the image. The solution proposed here is based on a non-linear transformation, acting as an adaptive histogram equalization of the local differences, in the hypothesis of gaussian distributions. The obtained results are closely related to other enhancement methods, with some advantage in the look-up filter implementation. The computational cost of the realization is evaluated, as well as the loss of performance determined by suboptimal block-processing and bilinear interpolation. Examples are referred in the contrast enhancement of C.T. images and digitized X-Rays.