Digital radiographs are often processed prior to printing or display. The algorithm used is generally a combination of contrast and edge enhancement applied in a spatially varying way. However, such enhancement often resulted in objectionable noise level in heavily attenuating regions, which may compromise the low contrast performance. We are developing and investigating a Scan Equalization Digital Radiography (SEDR) technique with which the transmitted x-ray exposure falling on the detector would be equalized and the image SNRs would be made more uniform. In this study, we simulated exposure equalization by acquiring a series of digital radiographs with incrementing mAs’ (0.25, 0.5, 1, 2, 4, 8) and then adding them with binary weighting factors to achieve equalized exposures over various regions of the image. The exposure-equalized image was then processed with two algorithms: local window/level optimization or edge enhancement using unsharp masking. The processed images with and without exposure equalization were then examined and compared with each other. For quantitative comparison, identically acquired images were used to obtain two sets of equalized and processed images. These two sets of images were subtracted from each other to generate a map of normalized noise for comparison. It is found that exposure equalization resulted in more uniform SNRs in both raw and processed images. Thus the noise levels in heavily attenuated regions were kept low and had less objectionable appearance for visualization of low contrast objects.