This paper documents an approach to sea ice classification through a combination of methods, both algorithmic and heuristic. The resulting system is a comprehensive technique, which uses dynamic local thresholding as a classification basis and then supplements that initial classification using heuristic geophysical knowledge organized in expert systems. The dynamic local thresholding method allows separation of the ice into thickness classes based on local intensity distributions. Because it utilizes the data within each image, it can adapt to varying ice thickness intensities to regional and seasonal charges and is not subject to limitations caused by using predefined parameters.

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The motion imagery community would benefit from the availability of standard measures for assessing image interpretability. The National Imagery Interpretability Rating Scale (NIIRS) has served as a community standard for still imagery, but no comparable scale exists for motion imagery. Several considerations unique to motion imagery indicate that the standard methodology employed in the past for NIIRS development may not be applicable or, at a minimum, require modifications. Traditional methods for NIIRS development rely on a close linkage between perceived image quality, as captured by specific image interpretation tasks, and the sensor parameters associated with image acquisition. The dynamic nature of motion imagery suggests that this type of linkage may not exist or may be modulated by other factors. An initial study was conducted to understand the effects target motion, camera motion, and scene complexity have on perceived image interpretability for motion imagery. This paper summarizes the findings from this evaluation. In addition, several issues emerged that require further investigation:The effect of frame rate on the perceived interpretability of motion imagery Interactions between color and target motion which could affect perceived interpretability The relationships among resolution, viewing geometry, and image interpretability The ability of an analyst to satisfy specific image exploitation tasks relative to different types of motion imagery clips Plans are being developed to address each of these issues through direct evaluations. This paper discusses each of these concerns, presents the plans for evaluations, and explores the implications for development of a motion imagery quality metric.

The development of a motion imagery (MI) quality scale, akin to the National Image Interpretibility Rating Scale (NIIRS) for still imagery, would have great value to designers and users of surveillance and other MI systems. A multiphase study has adopted a perceptual approach to identifying the main MI attributes that affect interpretibility. The current perceptual study measured frame rate effects for simple motion imagery interpretation tasks of detecting and identifying a known target. By using synthetic imagery, there was full control of the contrast and speed of moving objects, motion complexity, the number of confusers, and the noise structure. To explore the detectibility threshold, the contrast between the darker moving objects and the background was set at 5%, 2%, and 1%. Nine viewers were to detect or identify a moving synthetic "bug" in each of 288 10-second clip. We found that frame rate, contrast, and confusers had a statistically significant effect on image interpretibility (at the 95% level), while the speed and background showed no significant effect. Generally, there was a significant loss in correct detection and identification for frame rates below 10 F/s. Increasing the contrast improved detection and at high contrast, confusers did not affect detection. Confusers reduced detection of higher speed objects. Higher speed improved detection, but complicated identification, although this effect was small. Higher speed made detection harder at 1 Frame/s, but improved detection at 30 F/s. The low loss of quality at moderately lower frame rates may have implications for bandwidth limited systems. A study is underway to confirm, with live action imagery, the results reported here with synthetic.

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