Modern imaging systems are highly sensitive in a large dynamic range, which can give images consisting of many signal levels. Presentation of such images with varying dynamic ranges on a display with a fixed number of greylevels is difficult without losing important visual information. This paper presents several algorithms for automatic dynamic range adaptation for images. All of the algorithms are suitable for and also implemented in realtime applications. They fall mainly into two categories: histogram modification techniques and frequency based techniques. Some of the algorithms are evaluated in a perception experiment, where the goal is to get the visually most attractive images, and the experiment shows that the frequency based techniques are superior to the histogram modification techniques. Some of the proposed algorithms have proven to give visually attractive images, where none or almost none of the important information is lost, for a large selection of images with varying dynamic ranges.