Radiographic image quality is important in the medical field since it can increase the visibility of anatomical structures and even improve the medical diagnosis. Because the image quality depends on contrast, noise, and spatial resolution, images with low contrast, a lot of noises, or low resolution will decrease image quality, leading to an incorrect diagnosis. Therefore, radiographic images should be enhanced to facilitate medical expertise in making correct diagnosis. In this paper, radiographic images are enhanced by hybrid algorithms based on the idea of combining three image processing techniques: Contrast Limited Adaptive Histogram Equalization for enhancing image contrast, Median Filter for removing noises, and Unsharp Masking for increasing spatial resolution. Two series of medical images consisting of 20 x-ray images and 20 computed radiography images are enhanced with this method. Peak Signal to Noise Ratio (PSNR) and image contrast are computed in order to measure image quality. The results indicate that the enhanced images have better PSNR.