The expectation maximization (EM) algorithm has received considerable attention in the area of positron emitted tomography (PET) as a restoration and reconstruction technique. In this paper, the restoration capabilities of the EM algorithm when applied to radiographic images is investigated. This application does not involve reconstruction. The performance of the EM algorithm is quantitatively evaluated using a "perceived" signal-to-noise ratio (SNR) as the image quality metric. This perceived SNR is based on statistical decision theory and includes both the observer's visual response function and a noise component internal to the eye-brain system. For a variety of processing parameters, the relative SNR (ratio of the processed SNR to the original SNR) is calculated and used as a metric to compare quantitatively the effects of the EM algorithm with two other image enhancement techniques: global contrast enhancement (windowing) and unsharp mask filtering. The results suggest that the EM algorithm's performance is superior when compared to unsharp mask filtering and global contrast enhancement for radiographic images which contain objects smaller than 4 mm.

Abslracl-The problem addressed is reconfiguration planning for a metamorphic robotic system composed of any number of hexagonal robots when a single obstacle with multiple indentations or "pockets" is embedded in the goal environment.We extend our earlier work on filling a single pocket in an obstacle to the case where the obstacle surface may contain multiple pockets. The planning phase of our algorithm first determines whether the obstacle pockets provide sufficient clearance for module movement, i.e., whether the obstacle is "admissible''. In this paper, we present algorithms that sequentially order indhidoal pockets and order module placement inside each pocker These algorithms ensure that every cell in each pocket is filled and that module deadlock and collision do not occur during reeonfiguration. This paper also provjdes a complete o%eniew of the planning stage that is executed prior to reconfiguration and presents a distributed reconfiguration schema for filling more than one obstacle pocket concurrently, followed by the envelopment of the entire obstacle. Lastly, we present examples of obstacles with multiple pockets that were successfullj filled using our distributed reconfiguration simulator.

This paper presents algorithms to plan the concurrent and collision-free movement of n hexagonal metamorphic robots (modules) over a contiguous surface in a hexagonal grid. The problem is complicated by the fact that the surface may include "non-concurrently traversable" segments, where narrow passages between surface cells may result in module collision, regardless of the space separating moving modules.We present a new algorithm to identify unoccupied cells that, when filled with modules, form bridges to span all nonconcurrently traversable segments of the surface. Our bridging algorithms have the added benefit of reducing the overall traversal time for a given surface. Additionally, we show that four modules are sufficient to bridge any contiguous non-concurrently traversable segment, allowing concurrent module movement with minimal inter-module spacing. Finally, we present the results of simulating our algorithms using a discrete event simulator.

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