This research integrates the techniques used for the display of high dynamic range pictorial imagery for the practical visualization of non-pictorial (scientific) imagery such as remote sensing, medical imaging, astronomical imaging, etc. for data mining and interpretation. Nine algorithms were utilized to overcome the problem associated with rendering high dynamic range image data to low dynamic range display devices, and the results were evaluated using psychophysical experiments. Two paired-comparison experiment judging preference and scientific usefulness and a target detection experiment were performed. The paired-comparison results indicate that the Zone System algorithm performs the best on average and the Local Color Correction method performs the worst for both paired-comparison experiments. The results show that the performance of different encoding schemes depend on the type of data being visualized. The correlation between the preference and scientific usefulness judgments (R² = 0.31) demonstrates that observers tend to use different criteria when judging the scientific usefulness versus image preference. The result of the target detection experiment illustrates that the detectability of targets in an image is greatly influenced by the rendering algorithm due to the inherent differences in tone mapping among the algorithms.