This paper introduces an adaptive GOP structure (AGS), which adaptively defines the GOP structure according to the time-varying temporal properties of video sequences, and thus improves the coding efficiency of the MPEG & ITU-T's Joint Scalable Video Coding (JSVC) scheme, the method proposed in this paper, which adaptively modifies the size of GOP based on the image characteristics of video sequence, improves the coding efficiency up to 0.77 dB compared to the JSVC JSVM (Joint Scalable Video Model).

This paper introduces a new frame-based bit-rate control scheme for bandwidth-adaptive video coding. Proposed method can accurately adapt to the rapid varying scene characteristics by reducing the number of occurrences of the extrapolations while updating the rate-distortion model used for determine the appropriate quantization steps.

In this paper, we suggest the interference cancellation (IC) technique suitable for turbo coded code division multiple access (CDMA) systems, that merges IC processes into turbo decoding processes to improve system performance and reduce system complexity. To ensure the reliability of the temporary decision bits for cancellation, we use cyclic redundancy code (CRC) check as a measure. Prior to design turbo coded CDMA system, we first derive the optimized polynomials of low-rate turbo codes appropriate to CDMA systems. According to the simulation results with setting the processing gain (PG) to 120, the turbo coded CDMA system with the proposed IC technique can accommodate 60 users over additive white Gaussian noise (AWGN) channel when signal to noise ratio (SNR) is about 2. 5 dB and required frame error ratio (FER) is 10-2. Compared this result with the performance of single user's system, it requires only additional 1 dB SNR.

An H.264-based selective FGS coding scheme is proposed. It selectively uses the interframe-prediction data inside the enhancement-layer only when those data can significantly reduce the temporal-redundancies. Since this minimizes the drift effects, the overall coding efficiency is improved. Simulations show that average PSNR of the proposed scheme is higher by 1-3 dB and 3-5 dB than those of the H.264-based FGS and the MPEG-4 video FGS profile, respectively.

This letter proposes a method to retrieve the original image X out of multiple sets of SI (Side Information) in distributed video coding (DVC). Using Turbo decoding methods, the most reliable segments from the decoded Yi's were selected for the composition of Y∞, whose conditional entropy H(X| Y∞) became much lower than any individual conditional entropy H(X| Yi). This proposal has improved the peak signal-to-noise ratio (PSNR) by 1.1 to 1.8 dB, compared to the conventional single SI-based approach.

The network duplicating can achieve significant improvements of the Local Area Network (LAN)'s performance, availability, and security. For LAN duplicating, a Dual-Path Ethernet Module (DPEM) is developed. Since a DPEM is simply located at the front end of any network device as a transparent add-on type independent hardware machine, it does not require sophisticated server reconfiguration. We examine the desirable properties and the characteristics on the Dual-LAN structure. Our evaluation results show that the developed scheme is more efficient than the conventional Single-LAN structures in various aspects.

In this letter, we propose a network-adaptive video streaming scheme based on cross-layered hop-by-hop video rate control in wireless multi-hop networks. We argue that existing end-to-end network-adaptive video rate control schemes, which utilize end-to-end statistics, exhibit serious performance degradation in severely interfered wireless network condition. To cope with this problem, in the proposed scheme, intermediate wireless nodes adjust video sending rate depending upon wireless channel condition measured at MAC (Medium Access Control) layer. Extensive experimental results from an IEEE 802.11a-based testbed show that the proposed scheme improves the perceptual video quality compared to an end-to-end scheme.

We propose a new channel adaptive distributed video coding algorithm, which is adaptive to time-varying available bitrate and packet loss ratio. The proposed method controls the quantization parameter according to channel condition of especially error-prone mobile channel. Simulation shows that the proposed algorithm outperforms the conventional rate-control-only algorithm.

Multiscale retinex is one of the most popular image enhancement methods. However, its control parameters, such as Gaussian kernel sizes, gain, and offset, should be tuned carefully according to the image contents. In this letter, we propose a new method that optimizes the parameters using practical swarm optimization and multi-objective function. The method iteratively verifies the visual quality (i.e. brightness, contrast, and colorfulness) of the enhanced image using a multi-objective function while subtly adjusting the parameters. Experimental results shows that the proposed method achieves better image quality qualitatively and quantitatively compared with other image enhancement methods.

Feedforward neural networks have been successfully developed and applied in many areas because of their universal approximation capability. However, there still remains the problem of determining a suitable network structure for the given task. In this paper, we propose a novel self-organizing neural network which automatically adjusts its structure according to the task. Utilizing both the constructive and the pruning procedures, the proposed algorithm finds a near-optimal network which is compact and shows good generalization performance. One of its important features is reliability, which means the randomness of neural networks is effectively reduced. The resultant networks can have suitable numbers of hidden neurons and hidden layers according to the complexity of the given task. The simulation results for the well-known function regression problems show that our method successfully organizes near-optimal networks.

Nonminimum phase systems are difficult to be controlled with a conventional PID-type controller because of their inherent characteristics of undershooting. A neuro-controller combined with a PID-type controller has been shown to improve the control performance of the nonminimum phase systems while maintaining stability. In this paper, we apply a multiobjective evolutionary optimization method for training the neuro-controller to reduce the undershooting of the nonminimum phase system. The computer simulation shows that the proposed multiobjective approach is very effective and suitable because it can minimize the control error as well as reduce undershooting and chattering. This method can be applied to many industrial nonminimum phase problems with ease.

In this letter, we propose a new no-reference blur estimation method in the frequency domain. It is based on computing the cumulative distribution function (CDF) of the Fourier transform spectrum of the blurred image and analyzing the relationship between its shape and the blur strength. From the analysis, we propose and evaluate six curve-shaped analytic metrics for estimating blur strength. Also, we employ an SVM-based learning scheme to improve the accuracy and robustness of the proposed metrics. In our experiments on Gaussian blurred images, one of the six metrics outperformed the others and the standard deviation values between 0 and 6 could be estimated with an estimation error of 0.31 on average.

Speeded up robust features (SURF) can detect/describe scale- and rotation-invariant features at high speed by relying on integral images for image convolutions. However, the time taken for matching SURF descriptors is still long, and this has been an obstacle for use in real-time applications. In addition, the matching time further increases in proportion to the number of features and the dimensionality of the descriptor. Therefore, we propose a fast matching method that rearranges the elements of SURF descriptors based on their entropies, divides SURF descriptors into sub-descriptors, and sequentially and analytically matches them to each other. Our results show that the matching time could be reduced by about 75% at the expense of a small drop in accuracy.

This paper presents a simplifying method of the two previous fault attacks to pairing and the Miller algorithms based on a practical fault assumption. Our experimental result shows that the assumption is feasible and easy to implement.

The development of a small and multiband antenna plays an important role in the rapidly growing mobile communication market. This paper presents the design of a novel small and wideband planar inverted F-antenna which simultaneously covers GSM850/GSM900/DCS1900/IMT2000/WLAN/DMB services. The proposed antenna consists of a main patch with a pair of slits and L-shaped patch, occupying a total volume of 15366 mm3. A very wide impedance bandwidth characteristic was achieved by optimizing both the gap distance between the feed line and L-shaped patch, and also the lengths and widths of a pair of slits on the main patch, which is excited by the modified CPW-fed line. The average gains at the frequencies of 850, 2000 and 2600 MHz were -2.51, -1.42 and -1.68 dBi, respectively. The overall shape of the radiation patterns is suitable for mobile communications.

We demonstrated the transmission over 80 km at 10 Gb/s by using the amplifier and electroabsorption-modulator integrated laser diode. Tilt-facet antireflection window is implemented, inside of which a monitor photodiode is monolithically integrated for accurate power regulation. To better control the amplifier-input power and to reduce the feedback of the amplified spontaneous emission, an attenuator is incorporated by means of the inner-window. By amplifying the modulated signal and compensating modulator-chirp by gain-saturation in the amplifier, high power optical transmission is achieved from a device with -10 dB attenuation at total laser and amplifier currents of 200 mA.

Speeded up robust features (SURF) can detect scale- and rotation-invariant features at high speed by relying on integral images for image convolutions. However, since the number of image convolutions greatly increases in proportion to the image size, another method for reducing the time for detecting features is required. In this letter, we propose a method, called ordinal convolution, of reducing the number of image convolutions for fast feature detection in SURF and compare it with a previous method based on sparse sampling.

To reduce perforamnce degradations of LR-WPANs due to interference from WLANs, this letter proposes a protocol to allow a piconet to switch an operating channel to an interference-free channel only for transmitting beacon frames. The proposed method does not only increase network performances because of hgh reliability of the beacon frames, but also increase overerall channel utilizations because of using even interfered-channels.

This paper proposes an efficient adaptive depth-map coding scheme for generating virtual-view images in 3D-video. Virtual-view images can be generated by view-interpolation based on the decoded depth-map of the image. The proposed depth-map coding scheme is designed to have a new gray-coding-based bit-plane coding method for efficiently coding the depth-map images on the object-boundary areas, as well as the conventional DCT-based coding scheme (H.264/AVC) for efficiently coding the inside area images of the objects or the background depth-map images. Simulation results show that the proposed coding scheme, in comparison with the H.264/AVC coding scheme, improves the BD-rate savings 6.77%-10.28% and the BD-PSNR gains 0.42 dB-0.68 dB. It also improves the subjective picture quality of synthesized virtual-view images using decoded depth-maps.

Since femtocells are deployed in a two tier cellular network, along with macrocells operating on the same channel, interference between them limits the overall performance of the network. Without any control of the femtocell operation, pre-deployed macrocells will experience severe interference, which is not consistent with the current femtocell deployment principle. In this paper, to resolve this problem, a mathematical framework that optimizes the downlink transmission power of femtocells is formulated. Based on the formulated framework, we derive the optimal value of the transmission power so that the transmission affects the pre-deployed macrocell's downlink performance at a minimum scale, while providing sufficient Quality of Service (QoS) to its served users. Furthermore, to reduce the complexity of the power control process, we propose an Interference Estimation scheme which approximates the interference levels between different pairs of macrocell and femtocell base stations. The feasibility of this estimation process is shown by deriving the lower and upper bound of the estimation error. Through simulations, compared to no power control, we show that our proposed method provides a 17.64% reduction in macro user's outage probability, 5.9 dB decrease of interference on cell-edge macrocell users, and a 1.41 times increase in average user throughput.