Recently enhancing the visual experience of the user has been a new trend for TV displays. This trend comes from the fact that changes of ambient illuminations while viewing a Liquid Crystal Display (LCD) significantly affect human impressions. However, psychological effects caused by the combination of displayed video image and ambient illuminations have not been investigated. In the present research, we clarify the relationship between ambient illuminations and psychological effects while viewing video image displayed on the LCD by using a questionnaire based semantic differential (SD) method and a factor analysis method. Six kinds of video images were displayed under different colors and layouts of illumination conditions and rated by 15 observers. According to the analysis, it became clear that the illumination control around the LCD with displayed video image, the feeling of 'activity' and 'evaluating' were rated higher than the feeling of fluorescent ceiling condition. In particular, simultaneous illumination control around the display and the ceiling enhanced the feeling of 'activity,' and 'evaluating' with keeping 'comfort.' Moreover, the feeling of 'activity' under the illumination control around the LCD and the ceiling condition while viewing music video image was rated clearly higher than that with natural scene video image.

For copyright protection, a watermark signal is embedded in host images with a secret key, and a correlation is applied to judge the presence of watermark signal in the watermark detection. This paper treats a discrete wavelet transform (DWT)-based image watermarking method under specified false positive probability. We propose a new watermarking method to improve the detection performance by using not only positive correlation but also negative correlation. Also we present a statistical analysis for the detection performance with taking into account the false positive probability and prove the effectiveness of the proposed method. By using some experimental results, we verify the statistical analysis and show this method serves to improve the robustness against some attacks.

In reconstruction-based super resolution, a high-resolution image is estimated using multiple low-resolution images with sub-pixel misalignments. Therefore, when only one low-resolution image is available, it is generally difficult to obtain a favorable image. This letter proposes a method for overcoming this difficulty for single- image super resolution. In our method, after interpolating pixel values at sub-pixel locations on a patch-by-patch basis by support vector regression, in which learning samples are collected within the given image based on local similarities, we solve the regularized reconstruction problem with a sufficient number of constraints. Evaluation experiments were performed for artificial and natural images, and the obtained high-resolution images indicate the high-frequency components favorably along with improved PSNRs.

Iris recognition is an important biometric method for personal identification. The accuracy of an iris recognition system highly depends on the success of an iris segmentation step. In this paper, a robust and accurate iris segmentation algorithm for closed-up NIR eye images is developed. The proposed method addressed problems of different characteristics of iris databases using local image properties. A precise pupil boundary is located with an adaptive thresholding combined with a gradient-based refinement approach. A new criteria, called a local signal-to-noise ratio (LSNR) of an edge map of an eye image is proposed for localization of the iris's outer boundary. The boundary is modeled with a weighted circular integral of LSNR optimization technique. The proposed method is experimented with multiple iris databases. The obtained results demonstrated that the proposed iris segmentation method is robust and desirable. The proposed method accurately segments iris region, excluding eyelids, eyelashes and light reflections against multiple iris databases without parameter tunings. The proposed iris segmentation method reduced false negative rate of the iris recognition system by half, compared to results obtained using Masek's method.

The traditional spectrum auctions require a central auctioneer. Then, the secondary users (SUs) can bid for spectrum in multiple auction or sealed auction way. In this paper, we address the problem of distributed spectrum sharing in the cognitive networks where multiple owners sell their spare bands to multiple SUs. Each SU equips multi-interface/multi-radio, so that SU can buy spare bands from multiple owners. On the other hand, each owner can sell its spare bands to serval SUs. There are two questions to be addressed for such an environment: the first one is how to select bands/the owners for each SU; the second one is how to decide the competitive prices for the multiple owners and multiple SUs. To this end, we propose a two-side multi-band market game theoretic framework to jointly consider the benefits of all SUs and owners. The equilibrium concept in such games is named core. The outcomes in the core of the game cannot be improved upon by any subset of players. These outcomes correspond exactly to the price-lists that competitively balance the benefits of all SUs and owners. We show that the core in our model is always non-empty. When the measurement of price takes discrete value, the core of the game is defined as discrete core. The Dynamic Multi-band Sharing algorithm (DMS) is proposed to converge to the discrete core of the game. With small enough measurement unit of price, the algorithm can achieve the optimal performance compared with centralized one in terms of the system utility.

This letter introduces a new fairness concept, namely proportional quasi-fairness and proves that the optimal end-to-end rate of a network utility maximization can be proportionally quasi-fair with a properly chosen network utility function for an arbitrary compact feasible set.

In wireless sensor networks, real-time data delivery schemes typically achieve the desired delivery speed by proactively performing one-hop lookahead. Recently, to reduce the deadline miss ratio with respect to the desired delivery speed, a study has proposed a real-time data delivery scheme based on proactively performing two-hop lookahead. However, the recent proposal might cause heavy message exchange overhead and high computing complexity in order to proactively obtain two-hop neighbor speed information in all sensor nodes whether data are delivered or not. In this paper, we propose a novel real-time data delivery scheme that applies on-demand multi-hop lookahead only around data forwarding paths. Hence, the scheme can provide lower deadline miss ratio for real-time data delivery with low message exchange overhead than existing schemes.

The non-reference method is widely useful for picture quality estimation on the decoder side. In other work, we discussed pure non-reference estimation using only the decoded picture, and we proposed quantitative estimation methods for mosquito noise and block artifacts. In this paper, we discuss the estimation method as it applies to the degradation of the temporal domain. In the proposed method, motion compensated inter-picture differences and motion vector activity are the basic parameters of temporal degradation. To obtain these parameters, accurate but unstable motion estimation is used with a 1/16 reduction of processing power. Similar values of the parameters in the pictures can be seen in the stable original picture, but temporal degradation caused by the coding increases them. For intra-coded pictures, the values increase significantly. However, for inter-coded pictures, the values are the same or decrease. Therefore, by taking the ratio of the peak frame and other frames, the absolute value of the temporal degradation can be estimated. In this case, the peak frame may be intra-coded. Finally, we evaluate the proposed method using coded pictures with different quantization.

We review our recent work on ultra-long-haul wavelength division multiplexed (WDM) transmission with high spectral efficiency (SE) employing tight pre-filtering and multi-symbol detection. We start the discussion with a theoretical evaluation of the SE limit of pre-filtered modulation in optical fiber communication systems. We show that pre-filtering induced symbol correlation generates a modulation with memory and thus, a higher SE limit than that of the original memory-less modulation. We also investigate the merits of utilizing the pre-filtering induced symbol correlation with multi-symbol detection to achieve high SE transmission. We demonstrate transoceanic WDM transmission of a pre-filtered polarization division multiplexed return-to-zero quaternary phased shift keying (PDM-RZ-QPSK) modulation format with multi-symbol detection, achieving 419% SE which is higher than the SE limit of the original memory-less PDM-RZ-QPSK format.

A differential cross-correlation cell ID identification algorithm is proposed for IEEE 802.16e OFDMA cellular system. The cell ID represents the number of the preamble selected by the base station in downlink mode. First, we construct the downlink (DL) preamble structure and signal model with carrier frequency offset (CFO) and channel effects. Next, in order to achieve the initial synchronization, a differential receiver with cross correlation for all preamble patterns is proposed to search for cell ID. Simulation results confirm that the proposed structure is suitable for ITU fading channels and outperforms the conventional cell search system.

To meet the increasing demand to expand wavelength division multiplexing (WDM) transmission capacity, ultrahigh spectral density coherent optical transmission employing multi-level modulation formats has attracted a lot of attention. In particular, ultrahigh multi-level quadrature amplitude modulation (QAM) has an enormous advantage as regards expanding the spectral efficiency to 10 bit/s/Hz and even approaching the Shannon limit. We describe fundamental technologies for ultrahigh spectral density coherent QAM transmission and present experimental results on polarization-multiplexed 256 QAM coherent optical transmission using heterodyne and homodyne detection with a frequency-stabilized laser and an optical phase-locked loop technique. In this experiment, Raman amplifiers are newly adopted to decrease the signal power, which can reduce the fiber nonlinearity. As a result, the power penalty was reduced from 5.3 to 2.0 dB. A 64 Gbit/s data signal is successfully transmitted over 160 km with an optical bandwidth of 5.4 GHz.

In this paper, we analyze the impact of channel estimation errors for both decode-and-forward (DF) and amplify-and-forward (AF) cooperative communication systems over Nakagami-m fading channels. Firstly, we derive the exact one-integral and the approximate expressions of the symbol error rate (SER) for DF and AF relay systems with different modulations. We also present expressions showing the limitations of SER under channel estimation errors. Secondly, in order to quantify the impact of channel estimation errors, the average signal-to-noise-ratio (SNR) gap ratio is investigated for the two types of cooperative communication systems. Numerical results confirm that our theoretical analysis for SER is very efficient and accurate. Comparison of the average SNR gap ratio shows that DF model is less susceptible to channel estimation errors than AF model.

This letter proposes a simple k-hop flooding scheme for the temporarily lost child node of a multicast tree in a mobile ad hoc network where a group of nodes move together within a bound. Through simulation, we show that our scheme improves the packet delivery ratio of MAODV to be comparable to the epidemic routing with only small additional duplicate packets.

This letter investigates the effects of spatial correlation on several multiple antenna schemes in multiuser environments. Using an order statistics upper bound on achievable capacity, we quantify the interaction among spatial correlation, spatial diversity, spatial multiplexing and multiuser diversity. Also, it is verified that the upper bound is tighter than asymptotic capacity when the number of users is relatively small.

Background subtraction is widely used in detecting moving objects; however, changing illumination conditions, color similarity, and real-time performance remain important problems. In this paper, we introduce a sequential method for adaptively estimating background components using Kalman filters, and a novel method for detecting objects using margined sign correlation (MSC). By applying MSC to our adaptive background model, the proposed system can perform object detection robustly and accurately. The proposed method is suitable for implementation on a graphics processing unit (GPU) and as such, the system realizes real-time performance efficiently. Experimental results demonstrate the performance of the proposed system.

Precise estimation of data distribution with a small number of sample patterns is an important and challenging problem in the field of statistical pattern recognition. In this paper, we propose a novel method for estimating multimodal data distribution based on the Gaussian mixture model. In the proposed method, multiple random vectors are generated after classifying the elements of the feature vector into subsets so that there is no correlation between any pair of subsets. The Gaussian mixture model for each subset is then constructed independently. As a result, the constructed model is represented as the product of the Gaussian mixture models of marginal distributions. To make the classification of the elements effective, a graph cut technique is used for rearranging the elements of the feature vectors to gather elements with a high correlation into the same subset. The proposed method is applied to a character recognition problem that requires high-dimensional feature vectors. Experiments with a public handwritten digit database show that the proposed method improves the accuracy of classification. In addition, the effect of classifying the elements of the feature vectors is shown by visualizing the distribution.

A self-calibrating per-pin phase adjuster, which does not require any feedback from the slave chip and a multi-phase clock in the master and slave chips, is proposed for a high speed parallel chip-to-chip interface with a source synchronous double data rate (DDR) signaling. It achieves not only per-pin phase adjustment but also 90° phase shift of a strobe signal for a source synchronous DDR signaling. For this self-calibration, the phase adjuster measures and compensates the only relative mismatched delay among channels by utilizing on-chip time-domain reflectometry (TDR). Thus, variable delay lines, finite state machines, and a test signal generator are additionally required for the proposed phase adjuster. In addition, the power-gating receiver is used to reduce the discontinuity effect of the channel including parasitic components of chip package. To verify the proposed self-calibrating per-pin phase adjuster, the transceivers with 16 data, strobe, and clock signals for the interface with a source synchronous DDR signaling were implemented by using a 60 nm 1-poly 3-metal CMOS DRAM process with a 1.5 V supply. Each phase skew between Strobe and 16 Data was corrected within 0.028UI at 1.6-Gb/s data rate in a point-to-point channel.

A solution-processed red-sensitive organic photoconductive device was demonstrated by using soluble nickel-phthalocyanine. We found that a ratio of four nickel-phthalocyanine regioisomers was important factor for the high optical-electrical conversion efficiency. A maximum external quantum efficiency of device of 0.83% was achieved by optimizing the device structure.

Some new generalized cyclotomic sequences defined by C. Ding and T. Helleseth are proven to exhibit a number of good randomness properties. In this paper, we determine the defining pairs of these sequences of length pm (p prime, m ≥ 2) with order two, then from which we obtain their trace representation. Thus their linear complexity can be derived using Key's method.

The H.264/AVC standard achieves significantly high coding efficiency if multiple block size Motion Estimation is adopted. However, the complexity of Motion Estimation and DCT is dramatically increased as a result. In previous work we propose an early mode decision algorithm to control the complexity, based on all-zero-blocks detection in 1616 size. In this paper, we improve the algorithm. Firstly, we propose to detect all-zero blocks in 1616, 88 and 44 sizes to simplify the course of mode decision. Secondly, we define the thresholds which are used to terminate motion estimation and mode decision in advance for these sizes. Last, we present the whole proposed algorithm. Experiments show that about 77% encoding time and 85% motion estimation time can be saved on average, which is better than state-of-the-art approaches.