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.
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
223678
Automatic classification of digestive organs in wireless capsule endoscopy videos
Wireless Capsule Endoscopy (WCE) allows a physician to examine the entire small intestine without any surgical operation. With the miniaturization of wireless and camera technologies the ability comes to view the entire gestational track with little effort. Although WCE is a technical break-through that allows us to access the entire intestine without surgery, it is reported that a medical clinician spends one or two hours to assess a WCE video, It limits the number of examinations possible, and incur considerable amount of costs. To reduce the assessment time, it is critical to develop a technique to automatically discriminate digestive organs such as esophagus, stomach, small intestinal (i.e., duodenum, jejunum, and ileum) and colon. In this paper, we propose a novel technique to segment a WCE video into these anatomic parts based on color change pattern analysis. The basic idea is that the each digestive organ has different patterns of intestinal contractions that are quantified as the features. We present the experimental results that demonstrate the effectiveness of the proposed 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.
14295071
Sample Complexity of Real-Coded Evolutionary Algorithms
Researchers studying Evolutionary Algorithms and their applications have always been confronted with the sample complexity problem. The relationship between population size and global convergence is not clearly understood. Population size is usually chosen depending on researcher’s experience. In this paper, we study the population size using Probably Approximately Correct (PAC) learning theory. A ruggedness measure for fitness functions is defined. A sampling theorem that theoretically determines an appropriate population size towards effective convergence is proposed. Preliminary experiments show that the initial population of the proposed size provides good starting point(s) for searching the solution space and thus leads to finding global optima.
1221771
Multi-scale feature identification using evolution strategies
An image usually contains a number of different features and regions. Many image-related applications, such as content-based image retrieval and MRI-based diagnosis, often require the ability to identify and mark features within the image. For images containing a specific sort of feature (e.g. convective storm) or region (e.g. earthquake debris), that feature or region is always located adjacent to other features and regions on the image. A generic framework for automatically identifying features in images based on evolutionary computation is proposed here. The significant characteristic of the method is that it does not require segmentation. We use evolution strategies as the optimization algorithm to identify features. The system is based on a conjecture that certain filters will give prominent responses to certain features. The identified features are represented as regions enclosed within the chosen search structure-the ellipse. By defining filter response criteria as the fitness function, evolution strategies succeeds in finding the feature in a much more efficient way than, say, segmentation.
12895532
Volume cutout
We present a novel method for cutting out 3D volumetric structures based on simple strokes that are drawn directly on volume rendered images. The freehand strokes roughly mark out objects of interest and background. Our system then automatically segments the regions of interest and refines their boundaries in the rendered image. These 2D segmentation results provide constraints for 3D segmentation in the volume dataset. The objects of interest are then efficiently cut out from the volume via a combination of our novel two-pass graph cuts algorithm and the pre-computed over-segmentation. Our method improves traditional, fully automatic segmentation by involving human users in the process, yet minimizing user input and providing timely feedback. Our experiments show that our method extracts volumetric structures precisely and efficiently while requiring little skill or effort from the user.
3592511
An Array Data Flow Analysis Based Communication Optimizer
We present an efficient array data flow analysis based global communication optimizer which manages the analysis cost by partitioning the data flow problems into subproblems and solving the subproblems one at a time in a demand driven manner. In comparison to traditional array data flow based techniques, our scheme greatly reduces the memory requirement and manages the analysis time more effectively. The optimizer performs message vectorization, global redundant communication elimination and global communication scheduling. Our experience with the optimizer suggests that array data flow analysis for communication optimization is efficient and effective.
9042719
Using a Swap Instruction to Coalesce Loads and Stores
A swap instruction, which exchanges a value in memory with a value of a register, is available on many architectures. The primary application of a swap instruction has been for process synchronization. As an experiment we wished to see how often a swap instruction can be used to coalesce loads and stores to improve the performance of a variety of applications. The results show that both the number of accesses to the memory system (data cache) and the number of executed instructions are reduced.
33385860
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 for clusters of workstations. Realizing collective communication over reliable multicast can achieve higher performance than over reliable unicast primitives. 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 special features of local area networks (LANs) on the performance of 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 present our implementation of 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. The protocols are implemented over IP multicast using the standard UDP interface. We evaluate the performance of the protocols over Ethernet-connected networks, study the impact of some special features of the Ethernet on the performance of the protocols and investigate the methods to exploit these features to improve communication performance.
7786721
Geometry completion and detail generation by texture synthesis
We present a novel method for patching holes in polygonal meshes and synthesizing surfaces with details based on existing geometry. The most novel feature of our proposed method is that we transform the 3D geometry synthesis problem into a 2D domain by parameterizing surfaces and solve this problem in that domain. We then derive local geometry gradient images that encode intrinsic local geometry properties, which are invariant to object translation and rotation. The 3D geometry of holes is then reconstructed from synthesized local gradient images. This method can be extended to execute other mesh editing operations such as geometry detail transfer or synthesis. The resulting major benefits of performing geometry synthesis in 2D are more flexible and robust control, better leveraging of the wealth of current 2D image completion methods, and greater efficiency.