Abstract
Several display techniques were compared for representing scientific data in the context of a feature detection task. The data sets were rendered on a Silicon Graphics workstation using four display formats: linearized gray scale; rainbow scale; reduced hue (blue-green-yellow-white) scale; and a 3D-topographic format viewed in stereo. The task involved searching for features that were embedded in scientific data sets consisting of two spatial and one scalar variable. Data sets were drawn from three scientific domains: Landsat, medical MRI, and global atmospheric data bases. Two types of features were embedded within the data sets: circular (blob-like) discontinuities, and linear (cliff-like) discontinuities. Results showed a general advantage for the gray scale, and a marked disadvantage for the 3D-topographic format in both accuracy and response latency. Performance in the two color scale formats was intermediate, with the reduced hue scale supporting faster, if not more accurate performance than the full rainbow scale. Performance differences were found across data base domains, as well. Directions for future research are discussed.
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