Processing Color in Astronomical Imagery

Every year, hundreds of images from telescopes on the ground and in space are released to the public, making their way into popular culture through everything from computer screens to postage stamps. Most astronomical images are natively digital, with their data traveling from telescopes to scientists as a series of ones and zeroes and with tens and even hundreds of terabytes of data available from a single observatory archive (Brunner, 2001). These data span the entire electromagnetic spectrum from radio waves to infrared light to X-rays and gamma rays – a majority of which is undetectable to the human eye without technology. Once these data are collected, one or more specialists (scientists and other professionals) must process the data to create an image. Therefore, the creation of astronomical imagery involves a series of choices. How do these choices affect the comprehension of the science behind the images? What is the best way to represent data to a non-expert? Should these choices be based on aesthetics, scientific veracity, or is it possible to satisfy both? This paper reviews just one choice out of the many made by astronomical image processors: color. The choice of color is one of the most fundamental when creating an image taken with modern telescopes. We briefly explore the concept of the image as translation, particularly in the case of astronomical images from invisible portions o