The motion imagery community would benefit from 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, requires modifications. The dynamic nature of motion imagery introduces a number of factors that do not affect the perceived interpretability of still imagery—namely target motion and camera motion. We conducted a series of evaluations to understand and quantify the effects of critical factors. This paper presents key findings about the relationship of perceived interpretability to ground sample distance, target motion, camera motion, and frame rate. Based on these findings, we modified the scale development methodology and validated the approach. The methodology adapts the standard NIIRS development procedures to the softcopy exploitation environment and focuses on image interpretation tasks that target the dynamic nature of motion imagery. This paper describes the proposed methodology, presents the findings from a methodology assessment evaluation, and offers recommendations for the full development of a scale for motion imagery.
Motion imagery will play a critical role in future intelligence and military missions. The ability to provide a real time, dynamic view and persistent surveillance makes motion imagery a valuable source of information. The ability to collect, process, transmit, and exploit this rich source of information depends on the sensor capabilities, the available communications channels, and the availability of suitable exploitation tools. While sensor technology has progressed dramatically and various exploitation tools exist or are under development, the bandwidth required for transmitting motion imagery data remains a significant challenge. This paper presents a user-oriented evaluation of several methods for compression of motion imagery. We explore various codecs and bitrates for both inter- and intra-frame encoding. The analysis quantifies the effects of compression in terms of the interpretability of motion imagery, i.e., the ability of imagery analysts to perform common image exploitation tasks. The findings have implications for sensor system design, systems architecture, and mission planning.
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. Previous studies have explored the factors affecting the perceived interpretability of motion imagery and the ability to perform various image exploitation tasks. More recently, a study demonstrated an approach for adapting the standard NIIRS development methodology to motion imagery. This paper presents the first step in implementing this methodology, namely the construction of the perceived interpretability continuum for motion imagery. We conducted an evaluation in which imagery analysts rated the interpretability of a large number of motion imagery clips. Analysis of these ratings indicates that analysts rate the imagery consistently, perceived interpretability is unidimensional, and that interpretability varies linearly with log(GSD). This paper presents the design of the evaluation, the analysis and findings, and implications for scale development.
A fundamental problem in image processing is finding objective metrics that parallel human perception of image
quality. In this study, several metrics were examined to quantify compression algorithms in terms of perceived loss
of image quality. In addition, we sought to describe the relationship of image quality as a function of bit rate. The
compression schemes used were JPEG2000, MPEG2, and H.264. The frame size was fixed at 848x480 and the
encoding varied from 6000 k bps to 200 k bps. The metrics examined were peak signal to noise ratio (PSNR),
structural similarity (SSIM), edge localization metrics, and a blur metric. To varying degrees, the metrics displayed
desirable properties, namely they were monotonic in the bit rate, the group of pictures (GOP) structure could be
inferred, and they tended to agree with human perception of quality degradations. Additional work is being
conducted to quantify the sensitivity of these measures with respect to our Motion Imagery Quality Scale.
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, requires modifications. The dynamic nature of motion imagery introduces a number of factors that do not affect the perceived interpretability of still imagery - namely target motion and camera motion. A set of studies sponsored by the National Geospatial-Intelligence Agency (NGA) have been conducted to understand and quantify the effects of critical factors. This study discusses the development and validation of a methodology that has been proposed for the development of a NIIRS-like scale for motion imagery. The methodology adapts the standard NIIRS development procedures to the softcopy exploitation environment and focuses on image interpretation tasks that target the dynamic nature of motion imagery. This paper describes the proposed methodology, presents the findings from a methodology assessment evaluation, and offers recommendations for the full development of a scale for motion imagery.
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.
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.
This study developed texture extraction techniques for classifying natural background scenes using singular values features. Singular values (obtained using singular value decomposition) were used to produce a reduced one-dimensional feature space of texture attributes of natural scene regions. Scenes with tree, grass, and water regions were taken from FLIR imagery. Classification error was determined using a Bayes error estimate and Bhattacharyya distance was used to quantify separation of features between regions. Although there were variations within regional texture samples, good classification results were obtained using the singular value features.
This paper describes the design and testing of an indexing system for optical-beam steering. The cryogenic beam-steering mechanism is a 360-degree rotation device capable of discrete, high-precision alignment positions. It uses low-precision components for its rough alignment and kinematic design to meet its stringent repeatability and stability requirements (of about 5 arcsec). The principal advantages of this design include a decoupling of the low-precision, large angular motion from the high-precision alignment, and a power-off alignment position that potentially extends the life or hold time of cryogenic systems. An alternate design, which takes advantage of these attributes while reducing overall motion, is also presented. Preliminary test results show the kinematic mount capable of sub-arc second repeatability.
A proposed baseline design for the Space Infrared Telescope Facility includes a Tertiary Mirror Assembly (TMA)
which selectively redirects the telescope's converging science beam to each of several instruments. The TMA's mirror
rotates on an axis coincident with the beam's axis,'and is held steady during observation by a kinematic mount. A
bearing has been designed whose compliance causes minimal interference with the precision of the kinematic mount, and
which is well suited to the particular requirements of a cryogenic sateffite such as SIRTF. The bearing suspends its rotor
by taking advantage of the repulsion between a superconductor and a magnet. It potentially eliminates problems
associated with mechanical bearings that arise in similar applications, such as lubricant loss or failure, bearing wear, and
sensitivity to particulates, and does so without imposing the thermal load of a bearing heater or active magnetic bearing.
The bearing shows promise of offering an alternative to ball bearings in cryogenic applications where some compliance
is acceptable or advantageous.
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