Due to the growing popularity of High Dynamic Range (HDR) images and HDR displays, a large amount of existing Low Dynamic Range (LDR) images are required to be converted to HDR format to benefit HDR advantages, which give rise to some LDR to HDR algorithms. Most of these algorithms especially tackle overexposed areas during expanding, which is the potential to make the image quality worse than that before processing and introduces artifacts. To dispel these problems, we present a new LDR to HDR approach, unlike the existing techniques, it focuses on avoiding sophisticated treatment to overexposed areas in dynamic range expansion step. Based on a separating principle, firstly, according to the familiar types of overexposure, the overexposed areas are classified into two categories which are removed and corrected respectively by two kinds of techniques. Secondly, for maintaining color consistency, color recovery is carried out to the preprocessed images. Finally, the LDR image is expanded to HDR. Experiments show that the proposed approach performs well and produced images become more favorable and suitable for applications. The image quality metric also illustrates that we can reveal more details without causing artifacts introduced by other algorithms.

Ultra-wideband (UWB) pulse radar has high range resolution and permeability in a dielectric medium, and has great potential for the non-destructive inspection or early-stage detection of breast cancer. As an accurate and high-resolution imaging method for targets embedded in a dielectric medium, extended range points migration (RPM) has been developed. Although this method offers an accurate internal target image in a homogeneous media, it assumes the permittivity of the dielectric medium is given, which is not practical for general applications. Although there are various permittivity estimation methods, they have essential problems that are not suitable for clear, dielectric boundaries like walls, or is not applicable to an unknown and arbitrary shape of dielectric medium. To overcome the above drawbacks, we newly propose a permittivity estimation method suitable for various shapes of dielectric media with a clear boundary, where the dielectric boundary points and their normal vectors are accurately determined by the original RPM method. In addition, our method iteratively compensates for the scattered waveform deformation using a finite-difference time domain (FDTD) method to enhance the accuracy of the permittivity estimation. Results from a numerical simulation demonstrate that our method achieves accurate permittivity estimation even for a dielectric medium of wavelength size.

A method for the specification of weighting functions for a spaceborne/airborne interferometric synthetic aperture radar (SAR) sensor for Earth observation and environment monitoring is introduced. This method is based on designing an optimum mismatched filter which minimizes the total power in sidelobes located out of a specified range region around the peak value point of the system point-target response, i.e. impulse response function under the constraint imposed on the peak value. It is shown that this method allows achieving appreciable improvement in accuracy performance without degradation in the range resolution.

MIMO two-way multi-hop networks are considered in which the radio resource is fully reused in all multi-hop links to increase spectrum efficiency while the adjacent interference signals are cancelled by MIMO processing. In addition, the nodes in the multi-hop network optimize their transmit powers to mitigate the remaining overreach interference. Our main contribution in this paper is to investigate an efficient relay placement method with power allocation in such networks. We present two formulations, namely QoS-constrained optimization and SINR balancing, and solve them using a sequential geometric programming method. The proposed algorithm takes advantage of convex optimization to find an efficient configuration. Simulation results show that relay placement has an important impact on the effectiveness of power allocation to mitigate the interference. Particularly, we found that an uniform relay location is optimal only in power-limited scenarios. With optimal relay locations, significant end-to-end rate gain and power consumption reduction are achieved by SINR balancing and QoS-constrained optimization, respectively. Furthermore, the optimal number of hops is investigated in power or interference-limited scenarios.

Parametric images can help investigate disease mechanisms and vital functions. To estimate parametric images, it is necessary to obtain the tissue time activity curves (tTACs), which express temporal changes of tracer activity in human tissue. In general, the tTACs are calculated from each voxel's value of the time sequential PET images estimated from dynamic PET data. Recently, spatio-temporal PET reconstruction methods have been proposed in order to take into account the temporal correlation within each tTAC. Such spatio-temporal algorithms are generally quite computationally intensive. On the other hand, typical algorithms such as the preconditioned conjugate gradient (PCG) method still does not provide good accuracy in estimation. To overcome these problems, we propose a new spatio-temporal reconstruction method based on the dynamic row-action maximum-likelihood algorithm (DRAMA). As the original algorithm does, the proposed method takes into account the noise propagation, but it achieves much faster convergence. Performance of the method is evaluated with digital phantom simulations and it is shown that the proposed method requires only a few reconstruction processes, thereby remarkably reducing the computational cost required to estimate the tTACs. The results also show that the tTACs and parametric images from the proposed method have better accuracy.

This paper presents an approach based on character recognition to searching for keywords in on-line handwritten Japanese text. It employs an on-line character classifier and an off-line classifier or a combined classifier, which produce recognition candidates, and it searches for keywords in the lattice of candidates. It integrates scores to individually recognize characters and their geometric context. We use quadratic discriminant function(QDF) or support vector machines(SVM) models to evaluate the geometric features of individual characters and the relationships between characters. This paper also presents an approach based on feature matching that employs on-line or off-line features. We evaluate three recognition-based methods, two feature-matching-based methods, as well as ideal cases of the latter and concluded that the approach based on character recognition outperformed that based on feature matching.

In this paper, we consider a problem of simultaneously optimizing a sequence of graphs and a route which exhaustively visits the vertices from each pair of successive graphs in the sequence. This type of problem arises from repetitive routing of grasp-and-delivery robots used in the production of printed circuit boards. The problem is formulated as follows. We are given a metric graph G*=(V*,E*), a set of m+1 disjoint subsets Ci ⊆ V* of vertices with |Ci|=n, i=0,1,...,m, and a starting vertex s ∈ C0. We seek to find a sequence π=(Ci1, Ci2, ..., Cim) of the subsets of vertices and a shortest walk P which visits all (m+1)n vertices in G* in such a way that after starting from s, the walk alternately visits the vertices in Cik-1 and Cik, for k=1,2,...,m (i0=0). Thus, P is a walk with m(2n-1) edges obtained by concatenating m alternating Hamiltonian paths between Cik-1 and Cik, k=1,2,...,m. In this paper, we show that an approximate sequence of subsets of vertices and an approximate walk with at most three times the optimal route length can be found in polynomial time.

A simple and efficient reduced-reference video quality assessment method based on the activity-difference of DCT coefficients is proposed. The method provides better accuracy, monotonicity, and consistent predictions than the PSNR full-reference metric and comparable results with the full-reference SSIM. It also shows an improved performance to a similar VQ technique based on the calculation of the pixel luminance differences performed in the spatial-domain.

Spectrum sharing cognitive radio (CR) with maximal ratio combining (MRC) diversity under asymmetric fading is studied. Specifically, the channel on the secondary transmitter (STx) to the secondary receiver (SRx) link is Nakagami-m distributed while the channel on the STx to the primary receiver (PRx) link is Rayleigh distributed, and the channel state information (CSI) on the STx-PRx link is assumed to be outdated due to feedback delay. The outage capacity of the secondary user (SU) is derived under the average interference and peak transmit power constraints. The results supported by simulations are presented and show the effects of various system parameters on the outage capacity. Particularly, it is shown that the outdated CSI has no impact on the outage capacities in the cases of low peak transmit power constraint and zero-outage probability. It is also shown that MRC diversity can significantly improve the outage capacity especially for the zero-outage capacity and the outage capacity under low outage probability.

Congestion inherently occurs on the Internet due to traffic concentration on certain nodes or links of networks. The traffic concentration is caused by inefficient use of topological information of networks in existing routing protocols, which reduces to inefficient mapping between traffic demands and network resources. Actually, the route with minimum cost, i.e., number of hops, selected as a transmission route by existing routing protocols would pass through specific nodes with common topological characteristics that could contribute to a large improvement in minimizing the cost. However, this would result in traffic concentration on such specific nodes. Therefore, we propose a measure of the distance between two nodes that is suitable for reducing traffic concentration on specific nodes. To consider the topological characteristics of the congestion points of networks, we define node-to-node distance by using a generalized norm, p-norm, of a vector of which elements are degrees of intermediate nodes of the route. Simulation results show that both the maximum Stress Centrality (SC) and the coefficient of variation of the SC are minimized in some network topologies by selecting transmission routes based on the proposed measure of node-to-node distance.

BRISK (Binary Robust Invariant Scalable Keypoints) works dramatically faster than well-established algorithms (SIFT and SURF) while maintaining matching performance. However BRISK relies on intensity, color information in the image is ignored. In view of the importance of color information in vision applications, we propose CBRISK, a novel method for taking into account color information during keypoint detection and description. Instead of grayscale intensity image, the proposed approach detects keypoints in the photometric invariant color space. On the basis of binary intensity BRISK (original BRISK) descriptor, the proposed approach embeds binary invariant color presentation in the CBRISK descriptors. Experimental results show that CBRISK is more discriminative and robust than BRISK with respect to photometric variation.

In this paper, we give some results towards the conjecture that σ2t+1l-1,2t are the only nonlinear balanced elementary symmetric Boolean functions where t and l are positive integers. At first, a unified and simple proof of some earlier results is shown. Then a property of balanced elementary symmetric Boolean functions is presented. With this property, we prove that the conjecture is true for n=2m+2t-1 where m,t (m>t) are two non-negative integers, which verified the conjecture for a large infinite class of integer n.

The security of biometric authentication systems against impersonation attack is usually evaluated by the false accept rate, FAR. The false accept rate FAR is a metric for zero-effort impersonation attack assuming that the attacker attempts to impersonate a user by presenting his own biometric sample to the system. However, when the attacker has some information about algorithms in the biometric authentication system, he might be able to find a “strange” sample (called a wolf) which shows high similarity to many templates and attempt to impersonate a user by presenting a wolf. Une, Otsuka, Imai [22],[23] formulated such a stronger impersonation attack (called it wolf attack), defined a new security metric (called wolf attack probability, WAP), and showed that WAP is extremely higher than FAR in a fingerprint-minutiae matching algorithm proposed by Ratha et al. [19] and in a finger-vein-patterns matching algorithm proposed by Miura et al. [15]. Previously, we constructed secure matching algorithms based on a feature-dependent threshold approach [8] and showed that if the score distribution is perfectly estimated for each input feature data, then the proposed algorithms can lower WAP to a small value almost the same as FAR. In this paper, in addition to reintroducing the results of our previous work [8], we show that the proposed matching algorithm can keep the false reject rate (FRR) low enough without degrading security, if the score distribution is normal for each feature data.

Three-dimensional (3D) video service is expected to be introduced as a next-generation television service. Stereoscopic video is composed of two 2D video signals for the left and right views, and these 2D video signals are encoded. Video quality between the left and right views is not always consistent because, for example, each view is encoded at a different bit rate. As a result, the video quality difference between the left and right views degrades the quality of stereoscopic video. However, these characteristics have not been thoroughly studied or modeled. Therefore, it is necessary to better understand how the video quality difference affects stereoscopic video quality and to model the video quality characteristics. To do that, we conducted subjective quality assessments to derive subjective video quality characteristics. The characteristics showed that 3D video quality was affected by the difference in video quality between the left and right views, and that when the difference was small, 3D video quality correlated with the highest 2D video quality of the two views. We modeled these characteristics as a subjective quality metric using a training data set. Finally, we verified the performance of our proposed model by applying it to unknown data sets.

We extend the Nonparametric Discriminant Analysis (NDA) algorithm to a semi-supervised dimensionality reduction technique, called Semi-supervised Nonparametric Discriminant Analysis (SNDA). SNDA preserves the inherent advantages of NDA, that is, relaxing the Gaussian assumption required for the traditional LDA-based methods. SNDA takes advantage of both the discriminating power provided by the NDA method and the locality-preserving power provided by the manifold learning. Specifically, the labeled data points are used to maximize the separability between different classes and both the labeled and unlabeled data points are used to build a graph incorporating neighborhood information of the data set. Experiments on synthetic as well as real datasets demonstrate the effectiveness of the proposed approach.

We propose the asynchronous receiver-initiated MAC protocol with the stair-like sleep mode; each node reduces its own sleep time by the sleep-change-rate depending on the number of hops from the source to the sink in wireless sensor networks (WSNs). Using the stair-like sleep approach, our protocol achieves high delivery ratio, low packet delay, and high energy efficiency due to the reduction in idle listening time. Our protocol can formulate the upper bound of the idle listening time because of the feature that the sleep time decreases in a geometric progression, and the reduction of the idle listening time is obtained by using the stair-like sleep approach. In our proposed scheme, the sink calculates the sleep change rate based on the number of hops from the source to the sink. By using the control packets which have the role of the acknowledgment (ACK), our proposed protocol can achieve the stair-like sleep with no additional control packets. In addition, even in the network condition that multi-targets are detected, and the number of hops to the sink are changed frequently, our proposed protocol can change the sleep change rate adaptively because the sink can always obtain the number of hops from the source to the sink. Simulation results show that the proposed protocol can improve the performance in terms of the packet delivery ratio, the packet delay, and the energy efficiency compared to the conventional receiver-initiated MAC (RI-MAC) protocol.

Orthogonal frequency division multiplexing (OFDM) has great advantages such as high spectrum efficiency and robustness against multipath fading. In order to enhance the advantages, an Hermite-symmetric subcarrier coding for OFDM, which is used for transmission systems like the asymmetric digital subscriber line (ADSL) and multiband OFDM in ultra-wideband (UWB) communications, is very attractive. The subcarrier coding can force the imaginary part of the OFDM signal to be zero, then another data sequence can be simultaneously transmitted in the quadrature channel. In order to theoretically verify the effectiveness of the Hermite-symmetric subcarrier coding in wireless OFDM (HC-OFDM) systems, we derive closed-form equations for bit error rate (BER) and throughput over fading channels. Our analytical results can theoretically indicate that the HC-OFDM systems achieve the improvement of the performances owing to the effect of the subcarrier coding.

This paper presents comprehensive comparisons of the achievable throughput between the 32-/64-ary amplitude and phase shift keying (APSK) and cross 32QAM/square 64QAM schemes based on mutual information (MI) considering the peak-to-average power ratio (PAPR) of the modulated signal. As a PAPR criterion, we use a cubic metric (CM) that directly corresponds to the transmission back-off of a power amplifier. In the analysis, we present the best ring ratio for the 32 or 64APSK scheme from the viewpoint of minimizing the required received signal-to-noise power ratio (SNR) considering the CM that achieves the peak throughput, i.e., maximum error-free transmission rate. We show that the required received SNR considering the CM at the peak throughput is minimized with the number of rings of M = 3 and 4 for 32-ary APSK and 64-asry APSK, respectively. Then, we show with the best ring ratios that the (4, 12, 16) 32APSK scheme with M = 3 achieves a lower required received SNR considering the CM compared to that for the cross 32QAM scheme. Similarly, we show that the (4, 12, 20, 28) 64APSK scheme with M = 4 achieves almost the same required received SNR considering the CM as that for the square 64QAM scheme.

In this paper, we compare the decoding error rates in the error floors for non-binary low-density parity-check (LDPC) codes over general linear groups with those for non-binary LDPC codes over finite fields transmitted through the q-ary memoryless symmetric channels under belief propagation decoding. To analyze non-binary LDPC codes defined over both the general linear group GL(m, F2) and the finite field F2m, we investigate non-binary LDPC codes defined over GL(m3, F2m4). We propose a method to lower the error floors for non-binary LDPC codes. In this analysis, we see that the non-binary LDPC codes constructed by our proposed method defined over general linear group have the same decoding performance in the error floors as those defined over finite field. The non-binary LDPC codes defined over general linear group have more choices of the labels on the edges which satisfy the condition for the optimization.

Microwave imaging techniques, in particular synthetic aperture radar (SAR), are able to obtain useful images even in adverse weather or darkness, which makes them suitable for target position or feature estimation. However, typical SAR imagery is not informative for the operator, because it is synthesized using complex radio signals with greater than 1.0 m wavelength. To deal with the target identification issue for imaging radar, various automatic target recognition (ATR) techniques have been developed. One of the most promising ATR approaches is based on neural network classification. However, in the case of SAR images heavily contaminated by random or speckle noises, the classification accuracy is severely degraded because it only compares the outputs of neurons in the final layer. To overcome this problem, this paper proposes a self organized map (SOM) based ATR method, where the binary SAR image is classified using the unified distance matrix (U-matrix) metric given by the SOM. Our numerical analyses and experiments on 5 types of civilian airplanes, demonstrate that the proposed method remarkably enhances the classification accuracy, particular in lower S/N situations, and holds a significant robustness to the angular variations of the observation.