In recent years there have been many classes of sensors that provide a day/night, all-weather imaging and vision capability in a variety of sensing applications that enhance traditional, 3-color passive imagery. These sensors range from conventional night vision systems [1-4] to infrared imagers [5-7]. There are also instruments available that provide multiple spectral bands of information in the NIR, SWIR, MWIR, and LWIR, as well as polarimetric data in all of these wave bands [8]. With all of this available information, it is possible to develop robust and reliable target identification and detection processes. However, in many scenarios an observer does not need assistance with target detection; one simply needs a view of the world that allows one to make real-time decisions. This highlights one of the most significant limitations that prevent the widespread use of these emerging technologies. Most fusion schemes available today present too much data to the user in a way that is more confusing than helpful. Often times the data that are collected – such as polarization data or infrared spectral data – has no direct analog in human color vision. Furthermore, in many scenarios the data are fused in a way that does not take into account the workings of the human vision system.Our research team has been working with data from such sensors for many years. Of particular importance to us is the development of ergonomic display strategies. In particular, we have developed novel color mappings for spectral [9] and polarimetric imagery data [10] in the visible and infrared. Our previous work has focused on capturing and identifying orthogonal data sources and mapping them into orthogonal perceptual channels in order to preserve relationships among data. In addition to our work, there has been much effort at developing representation schemes that represent color and polarization intelligently [10,11].