William K. Krebs

Perceptual ability with real-world nighttime scenes: image-intensified, infrared, and fused-color imagery.

We investigated human perceptual performance allowed by relatively impoverished information conveyed in nighttime natural scenes. We used images of nighttime outdoor scenes rendered in image-intensified low-light visible (i2) sensors, thermal infrared (ir) sensors, and an i2/ir fusion technique with information added. We found that nighttime imagery provides adequate low-level image information for effective perceptual organization on a classification task, but that performance for exemplars within a given object category is dependent on the image type. Overall performance was best with the false-color fused images. This is consistent with the suggestion in the literature that color plays a predominate role in perceptual grouping and segmenting of objects in a scene and supports the suggestion that the addition of color in complex achromatic scenes aids the perceptual organization required for visual search. In the present study, we address the issue of assessment of perceptual performance with alternative night-vision sensors and fusion methods and begin to characterize perceptual organization abilities permitted by the information in relatively impoverished images of complex scenes. Applications of this research include improving night vision, medical, and other devices that use alternative sensors or degraded imagery.

Comparing behavioral receiver operating characteristic curves to multidimensional matched filters

Human factors experiments can be used to test whether a sensor can improve operator performance for detecting or recognizing a target.1 Although human factors experiments are of tremendous value, these tests are time consuming and resource intensive. To reduce costs associated with collecting behavioral data, a two-dimensional matched filter is proposed. The objective is to compare and contrast behavioral and matched filter receiver operating characteristic (ROC) plots to determine whether the matched filter technique is a good predictor of human performance. Five different background images (three infrared band images, a chromatic-fused image, and monochromatic-fused image) were used with, and without, a target (airplane) present. False alarm and target detection probabilities were computed and results were plotted on an ROC curve. The matched filter ROC curves were then compared to behavioral ROC curves. Results showed that the matched filter ROC curves were similar to behavioral ROC curves with color fusion, longwave infrared showing the highest sensitivity, and mid-wave and shortwave infrared scenes were significantly less sensitive (near chance). These results indicate that the matched filter analysis may be used to model human behavior.