Multi-spectral image portrayal using several sensors is a revolutionary way to increase the amount of useful visual
information to the end user. However, for maximum usability, the information from multiple sensors must be fused into
a single image that can be understood. The decisions about which sensors are delivering the most important information
for a given viewing situation and what manipulations should be done to the acquired data are complex. To better
examine this complexity, information was obtained from aviators about which visual tasks are deemed to be most
important. This information was gathered from discussions with pilots and other aircrew members as well as from
relevant publications. The important visual task information was then used to develop a matrix that included specific
visual aspects of the task (e.g., detection or identification). The matrix also included other parameters that could affect
or alter the ability to "see" the desired target or perform the task. These other parameters include ambient lighting,
environmental conditions (e.g., clear or hazy atmospheres), man-made impediments to vision (camouflage or smoke),
and which image enhancing algorithms should be applied (e.g., contrast enhancement or noise reduction). This top-down
evaluation was then used to determine which image enhancement algorithms are most important and which will be
employed most often for the identified visual tasks.
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