This paper presents an algorithm for fingerprint image restoration using Digital Reaction-Diffusion System (DRDS). The DRDS is a model of a discrete-time discrete-space nonlinear reaction-diffusion dynamical system, which is useful for generating biological textures, patterns and structures. This paper focuses on the design of a fingerprint restoration algorithm that combines (i) a ridge orientation estimation technique using an iterative coarse-to-fine processing strategy and (ii) an adaptive DRDS having a capability of enhancing low-quality fingerprint images using the estimated ridge orientation. The phase-only image matching technique is employed for evaluating the similarity between an original fingerprint image and a restored image. The proposed algorithm may be useful for person identification applications using fingerprint images.

An important area in visual communications is the restoration of image sequences degraded by channel and noise. Since a nonlinearity is commonly involved in image transmitting procedure, an adaptive nonlinear equalizer is required. In this paper we address this problem by proposing a 3D adaptive nonlinear filter, namely the 3D adaptive Volterra filter with an LMS type of adaptation algorithm. This adaptive filter is used for equalizing an unknown 2-D channel with some point-wise nonlinearity and restoring image sequences degraded by this channel. Prior to filtering, motion is estimated from the sequence and compensated for. For this purpose, a robust region-recursive Higher Order Statistics (HOS) based motion estimation method is employed. The overall combination is able to adequately remove undesired effects of communication channel and noise. The performance of this algorithm is examined using real image sequences demonstrated by experimental results.

This paper describes the requirements for fault recovery on photonic networks and proposes a fast restoration scheme for recovering optical networks. The proposed scheme is a type of pre-assignment restoration. The features of the scheme are that it is suitable for multi-recovery classes aimed at fine control of the optical paths and that it establishes harmonization between restoration control and distributed network control such as in IP networks. The scheme is implemented on Photonic multi protocol label switching (MPLS) routers. A restoration demonstration was performed and recovery was achieved within 500ms in the optical layer.

In this paper we study traffic engineering in Multiprotocol Label Switching (MPLS) networks. We consider off-line computation of disjoint working and restoration paths where path rerouting is used as the restoration scheme. We first compute maximum number of paths for each demand such that paths satisfy diversity requirements. Using the generated path set we study four different approaches for selecting working and restoration paths, and formulate each method as an Integer Linear Programming (ILP) problem. The first two methods treat working and restoration path design problems separately. We propose two new path design methods that jointly optimize the working and restoration paths. A traffic uncertainty model is developed in order to evaluate performances of these four approaches based on their robustness with respect to changing traffic patterns. We compare these design approaches based on the number of additional demands carried and the distribution of residual capacity over the network. It is shown through simulations that the weighted load balancing method proposed in this paper outperforms the other three methods in handling traffic demand uncertainty.

Polarimetric SAR interferometry has been successful and attractive for forest parameters (tree height and canopy extinction) estimation. In this paper, we propose to use the ESPRIT algorithm to extract the interferometric phase of local scatterers with polarimetric and interferometric SAR data. Two or three local scattering waves can be extracted at each image patch when a fully polarimetric data set (HH, HV, VV) is available. Furthermore, the ESPRIT can estimate two dominant local scattering centers when only a dual polarimetric data set (e.g., VV and VH) is provided. In order to demonstrate effectiveness the proposed technqiue, we examined the relation between local scattering centers extracted by this method and complex coherence of the coherent scattering model for vegetation cover. The results show that the three-wave estimation can be more accurate than the two-wave case. The extracted interferometric phases with full and dual polarization data sets correspond to effective ground and canopy scattering centers. In this investigation, SIR-C/X-SAR data of the Tien Shan flight-pass are used.

Antennas for Japanese terrestrial microwave relay links have been developed since the1950's and put into commercial use up to now in Japan. In particular, the path-length lens antennas developed in 1953 represents a monumental achievement for terrestrial microwave relay links, and the offset antenna for 256 QAM radio relay links developed in 1989 has the best electrical performance in the world. This paper reviews the antennas for Japanese terrestrial microwave relay links that have historical significance and describes the antenna design technologies developed in Japan.

Asymmetric networks, which provide asymmetric bandwidth or delay for upstream and downstream transfer, have recently gained much attention since they support popular applications such as the World Wide Web (WWW). HTTP (Hypertext Transfer Protocol) is the basis of most WWW services so, evaluating the performance of HTTP on asymmetric networks is increasingly important, particularly real-world networks. However, the performance of HTTP on the asymmetric networks composed of satellite and terrestrial links has not sufficiently evaluated. This paper proposes new formulas to evaluate the performance of both HTTP1.0 and HTTP1.1 on asymmetric networks. Using these formulas, we calculate the time taken to transfer web data by HTTP1.0/1.1. The calculation results are compared to the results of an existing theoretical formula and experimental results gained from a system that combines a VSAT (Very Small Aperture Terminal) satellite communication system for satellite links (downstream) and the Internet for terrestrial links (upstream). The comparison shows that the proposed formulas yield more accurate results (compared to the measured values) than the existing formula. Furthermore, this paper proposes an evaluation formula for pipelined HTTP1.1, and shows that the values output by the proposed formula agree with those obtained by experiments (on the VSAT system) and simulations.

In this letter, our proposed approach exploits the use of original and simplest Cellular Neural Network (CNN) for 2D Doubly Complementary (DC) Infinite Impulse Response (IIR) filter banks design. The properties of feedback and feedforward templates are studied for this purpose. Through some examples it is shown how generalizations of these templates can be used for DC IIR filter banks design. We modify Lagrangian function which is used for optimizing a low-pass filter design considering the constraint for stability of CNN. The brief conclusions with design examples that illustrate the proposed method and an image enhancement and restoration applications of designed filter banks are presented.

The reception quality of terrestrial digital broadcasting when the directional pattern of a mobile terminal is controlled has been experimentally evaluated using test signal. It was found that the reception probabilities with a controlled directional pattern were significantly improved over the case when an omni-directional antenna was used.

A new blind restoration method applying Real-coded genetic algorithm (RcGA) will be proposed, and this method will be proven valid for the blurred image restoration with unidentified degradation in the experiments. In this restoration method, the degraded and blurred image is going to get restricted to the images possible to be expressed in the point spread function (PSF), then the restoration filter for this degraded image, which is also the 2-dimentional inverse filter, will be searched among several points applying RcGA. The method will enable to seek efficiently among vast solution space consists of numeral coefficient filters. And perceiving the essential features of the spectrum in the frequency space, an evaluation function will be proposed. Also, it will be proposed to apply the Rolling-ball transform succeeding an appropriate Gaussian degrade function against the dual degraded image with blur convoluting impulse noise. By above stated features of this restoration method, it will enable to restore the degraded image closer to the original within a practical processing time. Computer simulations verify this method for image restoration problem when the factors causing image distortions are not identified.

Deforestation is a well-known program transformation technique which eliminates intermediate data structures that are passed between functions. One of its weaknesses is the inability to deforest programs using accumulating parameters. We show how certain kinds of intermediate lists produced by accumulating parameters can be deforested. In this paper we introduce an accumulative variant of foldr, called rdlof, and show the composition of functions defined by foldr and rdlof. As a simplified instance of foldr and rdlof, we then examine dmap, an accumulative extension of map, and give the corresponding fusion rules. While the associated composition rules cannot capture all deforestation problems, they can handle accumulator fusion of fold- and map-style functions in a simple manner. The rules for accumulator fusion presented here can also be viewed as a restricted composition scheme for attribute grammars, which in turn may help us to bridge the gap between the attribute and functional worlds.

This paper proposes a new method of retrieving images from large image databases. The method is based on VQ (Vector Quantization) of local texture features at interest points automatically detected in an image. The texture features are extracted by Gabor wavelet filter bank, and rearranged for rotation. These features are classified by VQ and then construct a pattern histogram. Retrievals are performed by just comparing pattern histograms between images.

Software with design flaws increases maintenance costs, decreases component reuse, and reduces software life. Even well-designed software tends to deteriorate with time as it undergoes maintenance. Work on restructuring object-oriented designs involves estimating the quality of the designs using metrics, and automating transformations that preserve the behavior of the designs. However, these factors have been treated almost independently of each other. A long-term goal is to define transformations preserving the behavior of object-oriented designs, and automate the transformations using metrics. In this paper, we describe a genetic algorithm based restructuring approach using metrics to automatically modify object-oriented designs. Cohesion and coupling metrics based on abstract models are defined to quantify designs and provide criteria for comparing alternative designs. The abstract models include a call-use graph and a class-association graph that represent methods, attributes, classes, and their relationships. The metrics include cohesion, inheritance coupling, and interaction coupling based on the behavioral similarity between methods extracted from the models. We define restructuring operations, and show that the operations preserve the behavior of object-oriented designs. We also devise a fitness function using cohesion and coupling metrics, and automatically restructure object-oriented designs by applying a genetic algorithm using the fitness function.

In interconnection networks, deadlock recovery has been studied in routing strategy. The routing strategy for the deadlock recovery is intended to optimize the routing performance when deadlocks do not occur. On the other hand, it is important to improve the routing performance by handling deadlocks if they occur. In this paper, a routing strategy for suspensive deadlock recovery called an escape-restoration routing is proposed and its performance is evaluated. In the principle of the proposed techniques, a small amount of exclusive buffer (escape-buffer) at each router is prepared for handling one of deadlocked packets. The transmission of the packet is suspended by temporarily escaping it to the escape-buffer. After the other deadlocked packets were sent, the suspended transmission resumes by restoring the escaped packet. Evaluation results show that the proposed techniques can improve the routing performance more than that of the previous recovery-based techniques in handling deadlocks.

Practical image restoration filters usually include a parameter that controls regularizability, trade-off between fidelity of a restored image and smoothness of it, and so on. Many criteria for choosing such a parameter have been proposed. However, the relation between these criteria and the squared error of a restored image, which is usually used to evaluate the restoration performance, has not been theoretically substantiated. Sugiyama and Ogawa proposed the subspace information criterion (SIC) for model selection of supervised learning problems and showed that the SIC is an unbiased estimator of the expected squared error between the unknown model function and an estimated one. They also applied it to restoration of images. However, we need an unbiased estimator of the unknown original image to construct the criterion, so it can not be used for general situations. In this paper, we present a modified version of the SIC as a new criterion for choosing a parameter of image restoration filters. Some numerical examples are also shown to verify the efficacy of the proposed criterion.

A new class of least-squares algorithms is presented for adaptive filtering. The idea is to use a fixed set of directions and perform line search with one direction at a time in a cyclic fashion. These algorithms are called Euclidean Direction Search (EDS) algorithms. The fast version of this class is called the Fast-EDS or FEDS algorithm. It is shown to have O(N) computational complexity and a convergence rate comparable to that of the RLS algorithm. Computer simulations are presented to illustrate the performance of the new algorithm.

We propose a new solvable Markov random field model for Bayesian image processing and give the exact expressions of the marginal likelihood and the restored image by using the multi-dimensional Gaussian formula and the discrete Fourier transform. The proposed Markov random field model includes the conditional autoregressive model and the simultaneous autoregressive model as a special case. The estimates of hyperparameters are obtained by maximizing the marginal likelihood. We study some statistical properties of the solvable Markov random field model. In some numerical experiments for standard images, we show that the proposed Markov random field model is useful for practical applications in image restorations. The investigation of probabilistic information processing by means of a solvable probabilistic model is recently in progress not only for image processing but also for error correcting codes and so on. The solvable probabilistic model gives us some important aspects for the availability of probabilistic computational systems.

Several methods have been developed for solving blind deconvolution problem. Recursive inverse filtering method is proposed recently and shown to have good convergence properties. This method requires accurate estimate of the region of support. In this paper, we propose to modify the original method by incorporating split, merge and grouping algorithm to find the region of support automatically.

The requirement to realize large-capacity, high-speed and guaranteed Quality of Service (QoS) communications in IP networks is a recent development. A technique to satisfy these requirements, Multi-Protocol Label Switching (MPLS) is the focus of this paper. In the future, it is expected that congestion and faults on a Label Switched Path (LSP) will seriously affect service contents because various applications are densely served in a large area. In MPLS, however, methods to solve these problems are not clear. Therefore, this study proposes a concrete traffic engineering method to avoid heavy congestion, and at the same time, endeavors to realize a fault-tolerant network by autonomous restoration, or self-healing.

Space-variant approaches subject to local image characteristics are useful in practical image restoration because many natural images are nonstationary. Motivated by the success of denoising approaches in the wavelet domain, we propose a region-adaptive restoration approach which adopts a wavelet denoising technique in flat regions after an under-regularized constrained least squares restoration. Experimental results verify that this approach not only improves image quality in mean square error but also contributes to ringing reduction.