12607560
Speckle reducing anisotropic diffusion
This paper provides the derivation of speckle reducing anisotropic diffusion (SRAD), a diffusion method tailored to ultrasonic and radar imaging applications. SRAD is the edge-sensitive diffusion for speckled images, in the same way that conventional anisotropic diffusion is the edge-sensitive diffusion for images corrupted with additive noise. We first show that the Lee and Frost filters can be cast as partial differential equations, and then we derive SRAD by allowing edge-sensitive anisotropic diffusion within this context. Just as the Lee and Frost filters utilize the coefficient of variation in adaptive filtering, SRAD exploits the instantaneous coefficient of variation, which is shown to be a function of the local gradient magnitude and Laplacian operators. We validate the new algorithm using both synthetic and real linear scan ultrasonic imagery of the carotid artery. We also demonstrate the algorithm performance with real SAR data. The performance measures obtained by means of computer simulation of carotid artery images are compared with three existing speckle reduction schemes. In the presence of speckle noise, speckle reducing anisotropic diffusion excels over the traditional speckle removal filters and over the conventional anisotropic diffusion method in terms of mean preservation, variance reduction, and edge localization.
40955801
Polarimetric SAR image segmentation using texture partitioning and statistical analysis
This paper presents a new technique for partitioning polarimetric synthetic aperture radar (POL-SAR) imagery into regions of homogeneous polarimetric backscattering properties. The method consists of two cascaded steps: an initial texture segmentation of one image derived from the POL-SAR data, and a polarimetric statistical region merging process that refines and modifies the initial segmentation. In the first stage, a morphological region-based image partitioning technique, the watershed algorithm, plays the key role. While in the second stage, the region adjacency graph and the segment dissimilarity measures derived from the Wishart model and the K distribution are applied. The overall segmentation algorithm has been tested using real 4-look POL-SAR imagery and sample results are provided in the paper. The main innovation of this work is the utilization of the K distribution in the segmentation process.
12275137
Dynamically Self-Organized Service Composition in Wireless Ad Hoc Networks
Service composition is a powerful tool to create new services rapidly by reusing existing ones. Previous research mainly focuses on the wired infrastructure-based environment. With the developments in mobile devices and wireless communication technology in recent years, mobile ad hoc network has received an increasing attention as a new communication paradigm. However, the existing service composition techniques do not work any longer in an ad hoc environment. In this paper, we present the service composition problem in wireless ad hoc network with full consideration of the characteristics of an ad hoc environment. To solve this problem, we develop two service composition routing algorithms, Simple Broadcasting Service Composition and Behavior Evolution Service Composition. The main contribution of our algorithms is that the whole process of service composition is done by the cooperation of nodes on-the-fly instead of a centralized broker to meet the peculiarity of ad hoc networks. Finally, we describe an initial implementation architecture for service composition in wireless ad hoc networks.
13290415
Quality-Based Software Reuse
Work in software reuse focuses on reusing artifacts. In this context, finding a reusable artifact is driven by a desired functionality. This paper proposes a change to this common view. We argue that it is possible and necessary to also look at reuse from a non-functional (quality) perspective. Combining ideas from reuse, from goal-oriented requirements, from aspect-oriented programming and quality management, we obtain a goal-driven process to enable the quality-based reusability.
15594560
FRM-Based FIR Filters with Minimum Coefficient Sensitivities
A method for optimizing FRM-based FIR filters with optimum coefficient sensitivity is presented. This technique can be used in conjunction with nonlinear optimization techniques to design very sharp filters that do not only have very sparse coefficient values but also very low coefficient sensitivity.
8525620
Failure insensitive routing for ensuring service availability
Intra-domain routing protocols employed in the Internet route around failed links by having routers detect adjacent link failures, exchange link state changes, and recompute their routing tables. Due to several delays in detection, propagation and recomputation, it may take tens of seconds to minutes after a link failure to resume forwarding of packets to the affected destinations. This discontinuity in destination reachability adversely affects the quality of continuous media applications such as Voice over IP. Moreover, the resulting service unavailability for even a short duration could be catastrophic in the world of e-commerce. Though careful tuning of the various parameters of the routing protocols can accelerate convergence, it may cause instability when the majority of the failures are transient. To improve the failure resiliency without jeopardizing the routing stability, we propose a local rerouting based approach called failure insensitive routing. Under this approach, upon a link failure, adjacent router suppresses global updating and instead initiates local rerouting. All other routers infer potential link failures from the packet's incoming interface, precompute interface specific forwarding We demonstrate that the proposed approach provides higher service availability than the existing routing schemes.
1372639
Motion Field Estimation for Temporal Textures
This paper presents a novel approach for estimating the flow fields of dynamic temporal textures whose motion differs radically from that of rigid bod- ies. Our approach is based on a local flow probability distribution function at each pixel using the STAR model and the data from a spatio-temporal neighborhood. The peak of this density function can be regarded as the estimated local flow vec- tor. Our complete algorithm exploits a two-stage process. The first stage of the algorithm applies a simple tensor method to estimate the direction of the optical flow at each pixel in the texture. In the second stage, the flow probability function is used to perform a one-dimensional search along the flow direction to obtain the magnitude. Performance analysis and experiments with real video sequences show that our methods can successfully estimate flow fields.