27055322
A Fast Evolution Strategies Based Approach To Image Registration
An image registration approach based on Evolution Strategies is proposed. In image registration, an invariant reference needs to be established within each source image, which is unavailable in many cases. To solve this problem, feature configuration (which is defined as the cluster of feature vectors on an image representing homogeneous feature distribution,) is employed to describe the object inside the scene. Instead of finding the correspondence of the entire image, the spatial relationships of the feature configuration in every source image are discovered with Evolution Strategies (ES). While one approach, even this one, may not be suitable for every image domain, the ES approach has many advantages. Compared to some methods, it is computationally effective; compared to other, it is capable of discovering transformations of larger scope (e.g., greater rotation angles or translation distances etc.) The search structure we use is an ellipsoid. The results from various images prove it to be an efficient and effective method.
6706494
Real-Time Sensor Fusion Framework for Distributed Intelligent Sensors
Multi-sensor data fusion has found widespread applications in industrial and research sectors. The purpose of real time multi-sensor data fusion is to dynamically estimate an improved system model from a set of different data sources, i.e., sensors. This paper presented a systematic and unified real time sensor fusion framework (RTSFF) based on distributed intelligent sensor network. The RTSFF is an open architecture which consists of four layers – the transaction layer, the process fusion layer, the control layer, and the planning layer. This paradigm facilitates distribution of intelligence to the sensor level and sharing of information among sensors, controllers, and other devices in the system. The transducer layer is populated with intelligent sensors. The learning ability of the intelligent sensor model enables it to extract characteristics of monitored signal. The representation issue is managed at this level. After describing the RTSFF, the paper then focuses on the fundamental units of the framework, the highly autonomous transducers.
124461239
Subband noise estimation for adaptive wavelet shrinkage
In this article, we present an adaptive image denoising method based on subband noise modeling. For wavelet shrinkage, choosing the threshold depends on correctly estimating the noise variance. By modeling the inter-subband noise variance with a parameterized normalized exponential function, the problem becomes identifying the maximum noise variance. Such a maximum exists in the highest decomposition level and can be estimated by locating the extreme of the first derivative of the subband variance function. The experiments demonstrate that our method outperforms peers, especially in the cases of large noise variance.
8920686
Population Sizing Based on Landscape Feature
Population size for EvolutionaryAlgorithms is usually an empirical parameter. We study the population size from aspects of fitness landscapes' ruggedness and Probably Approximately Correct (PAC) learning theory.
38619191
Function Granularity Estimation for Multimodal Optimization
In this article, we study the subspace function granularity and present a method to estimate the sharing distance and the optimal population size. To achieve multimodal function optimization, niching techniques diversify the population of Evolutionary Algorithms (EA) and encourage heterogeneous convergence to multiple optima. The key to a successful diversification is effective resource sharing. Without knowing the fitness landscape, resource sharing is usually determined by uninformative assumptions on the number of peaks. Using the Probably Approximately Correct (PAC) learning theory and the ∊-cover concept, a PAC neighborhood for a set of samples is derived. Within this neighborhood, we sample the fitness landscape and compute the subspace Fitness Distance Correlation (FDC) coefficients. Using the estimated granularity feature of the fitness landscape, the sharing distance and the population size are determined. Experiments demonstrate that by using the estimated population size and sharing distance an Evolutionary Algorithm successfully identifies multiple optima.
2765235
Volumetric tongue reconstruction by fusing bidirectional MR images
In this paper we describe a 3D reconstruction method that fuses sagittal and coronal images. In our volumetric MRI study of the human tongue, multiple contiguous slices were acquired in the sagittal and the coronal planes. A bidirectional linear interpolation method was developed that estimated target voxel value using weighted neighbor pixels in the bounding slices. A wavelet fusion method was then employed to integrate prominent subband coefficients. Experiments have shown that fusion-based image reconstruction reduced artifacts, greatly improved reconstruction accuracy, and enhanced image details. Our method casts new light on MR imaging and image processing that demand high resolution in a short acquisition time
8426908
Branch Elimination via Multi-variable Condition Merging
Conditional branches are expensive. Branches require a significant percentage of execution cycles since they occur frequently and cause pipeline flushes when mispredicted. In addition, branches result in forks in the control flow, which can prevent other code-improving transformations from being applied. In this paper we describe profile-based techniques for replacing the execution of a set of two or more branches with a single branch on a conventional scalar processor. First, we gather profile information to detect the frequently executed paths in a program. Second, we detect sets of conditions in frequently executed paths that can be merged into a single condition. Third, we estimate the benefit of merging each set of conditions. Finally, we restructure the control flow to merge the sets that are deemed beneficial. The results show that eliminating branches by merging conditions can significantly reduce the number of conditional branches performed in non-numerical applications.
16773627
Illustrating surfaces in volume
This paper presents a novel framework for illustrating surfaces in a volume. Surfaces are illustrated by drawing only feature lines, such as silhouettes, valleys, ridges, and surface hatching strokes, and are embedded in volume renderings. This framework promises effective illustration of both surfaces and volumes without occluding or cluttering each other. A two-step approach has been taken: the first step depicts surfaces; the second step performs volume rendering, at the same time embedding surfaces from the first step.
 We introduce Procedurally Perturbed Image Processing (PIP), a new method for enhancing both feature detection and depiction of surfaces. We also present implementation strategies, especially those leveraging modern graphics hardware, for delivering an interactive rendering system. Our implementation results have shown that this mixed form of rendering improves volume visualization and is efficient.
2841955
Constructing Inter-Domain Packet Filters to Control IP Spoofing Based on BGP Updates
The Distributed Denial-of-Service (DDoS) attack is a serious threat to the legitimate use of the Internet. Prevention mechanisms are thwarted by the ability of attackers to forge or spoof the source addresses in IP packets. By employing IP spoofing, attackers can evade detection and put a substantial burden on the destination network for policing attack packets. In this paper, we propose an inter-domain packet filter (IDPF) architecture that can mitigate the level of IP spoofing on the Internet. A key feature of our scheme is that it does not require global routing information. IDPFs are constructed from the information implicit in Border Gateway Protocol (BGP) route updates and are deployed in network border routers. We establish the conditions under which the IDPF framework correctly works in that it does not discard packets with valid source addresses. Based on extensive simulation studies, we show that, even with partial deployment on the Internet, IDPFs can proactively limit the spoofing capability of attackers. In addition, they can help localize the origin of an attack packet to a small number of candidate networks.
6360330
An empirical study of reliable multicast protocols over Ethernet-connected networks
Recent advances in multicasting over the Internet present new opportunities for improving communication performance in clusters of workstations. The standard IP multicast, however only supports unreliable multicast, which is difficult to use for building high level message passing routines. Thus, reliable multicast primitives must be implemented over the standard IP multicast to facilitate the use of multicast for high performance communication on clusters of workstations. Although many reliable multicast protocols have been proposed for the wide area Internet environment, the impact of architectural features of local area networks (LANs) on the reliable multicast protocols has not been thoroughly studied. Efficient reliable multicast protocols for LANs must exploit these features to achieve the best performance. In this paper we study four types of reliable multicast protocols: the ACK-based protocols, the NAK-based protocols with polling, the ring-based protocols, and the tree-based protocols. We evaluate the performance of the protocols over Ethernet-connected networks, study the impact of architectural features of the Ethernet on the performance of the protocols, and investigate the methods to exploit these features to achieve the best performance.
3570050
Algorithms for Supporting Compiled Communication
We investigate the compiler algorithms to support compiled communication in multiprocessor environments and study the benefits of compiled communication, assuming that the underlying network is an all-optical time-division-multiplexing (TDM) network. We present an experimental compiler, E-SUIF, that supports compiled communication for High Performance Fortran (HPF) like programs on all-optical TDM networks, and describe and evaluate the compiler algorithms used in E-SUIF. We further demonstrate the effectiveness of compiled communication on all-optical TDM networks by comparing the performance of compiled communication with that of a traditional communication method using a number of application programs.