SIMBAD references

The quality of modern astronomical data and the agility of current image-processing software enable the visualization of data in a way that exceeds the traditional definition of an astronomical image. Two developments in particular have led to a fundamental change in how astronomical images can be assembled. First, the availability of high-quality multiwavelength and narrowband data allow for images that do not correspond to the wavelength sensitivity of the human eye, thereby introducing ambiguity in the usage and interpretation of color. Second, many image-processing software packages now use a layering metaphor that allows for any number of astronomical data sets to be combined into a color image. With this technique, images with as many as eight data sets have been produced. Each data set is intensity-scaled and colorized independently, creating an immense parameter space that can be used to assemble the image. Since such images are intended for data visualization, scaling and color schemes must be chosen that best illustrate the science. A practical guide is presented on how to use the layering metaphor to generate publication-ready astronomical images from as many data sets as desired. A methodology is also given on how to use intensity scaling, color, and composition to create contrasts in an image that highlight the scientific detail. Examples of image creation are discussed.