Previous work has demonstrated the potential for adaptive filtration in processing digital chest images. The technique uses the histogram of the image to determine the pixels (and regions) in which edge enhancement is applied. This paper extends that work by investigating the choice of parameters used in selectively enhancing the mediastinum. The image is separated into its low and high frequency components by convolution with a square kernel. The effect of kernel size was studied with a choice of 17 x 17 mm, which was found to be sufficient to include the frequencies of interest. A serious deficiency in previous implementations of this technique is the existence of ringing artifacts at the juncture of the lung and mediastinum. These result in part from the use of a step function to specify the low frequency image intensity above which high frequencies are amplified. By replacing this step with a smoother (cosine) function, the artifact can be removed. Finally, the amplification constant was examined in light of its effect on both structure and noise in the image.