In Digital On-Channel Repeaters (DOCR) of Terrestrial-DMB (Digital Multimedia Broadcasting), there exist feedback signals generated from transmit antenna and re-entering at receive antenna. Therefore DOCR becomes unstable unless the feedback signal is properly eliminated. Previous research proposed a feedback canceller to estimate the feedback channel to deal with this problem. However formerly used estimation algorithms show unsatisfied performance in terms of convergence rate and quality although their implementations are simple. This paper applies PNLMS (Proportionate Normalized Least Mean Squares) adaptive algorithm to feedback channel estimation and evaluates the performances which solve the problem of feedback signal effectively.

In this paper, we propose a PSNR(peak-to-peak signal to noise ratio) estimation method exploiting visual rhythm information for the reconstructed video frames at the customer`s STB(Set-top Box). Key idea is that we can estimate the PSNR by using VR(visual rhythm) information even though a VR consists of the pixels in a vertical direction of a 2D(2-dimensional) video frame, because VR is the 1D projected version of a 2D video frame approximately. Simulation results show that the estimated PSNR from VR information is closely related to the PSNR from 2D video frames. The advantages of the proposed scheme includes that it can monitor the video quality efficiently while minimizing the computation load of STB, and show the location, duration and occurrence count of severe picture degradation.

With advances in video technology, many researchers are interested in video quality assessment to prove better performance of proposed algorithms. Since human visual system is too complex to be formulated exactly, many researches about video quality assessment are in progressing. No-reference video-quality assessment is suitable for various video streaming services, because of no requested additional data and network capacity to perform quality assessment. In this paper, we propose a novel no-reference video-quality assessment method with the estimation of dynamic range distortion. To measure the performance, we obtain mean opinion score (MOS) data by subject video quality test with the ITU-T P.910 Absolute Category Rating (ACR) method. And, we compare it with proposed algorithm using 363 video sequences. Experimental results show that the proposed algorithm has a higher correlation with obtained MOS.

In this paper, we propose a new relay selection algorithm for a two-way multiple relay channel. In the two-way multiple relay channel, two users exchange information with each other via multiple relays. The relays use a decode-and-forward or amplify-and-forward protocol, and exploit the combining process of the received packets to reduce the required channel resources. In the multiple relay network, diversity gain is achieved as the number of relays increases, and various schemes are proposed. In this paper, we propose a single best relay selection scheme based on instantaneous channel conditions. First of all, relays obtain the instantaneous channel state information in the handshaking process, and a single best relay is selected in a distributed methods prior to data transmissions. The relay selection metric is proposed so that the end-to-end channel condition is evaluated based on the intantaneous channel state informations. Simulation results show that the proposed relay selection algorithm achieve the increased throughput and diversity order when the number of potential relays is increased.

Recently, as the necessity of a light-weighted video encoding technique has been rising for applications such as UCC(User Created Contents) or Multiview Video, Distributed Video Coding(DVC) where a decoder, not an encoder, performs the motion estimation/compensation taking most of computational complexity has been vigorously investigated. Wyner-Ziv coding reconstructs an image by eliminating the noise on side information which is decoder-side prediction of original image using channel code. Generally the side information of Wyner-Ziv coding is generated by using frame interpolation between key frames. The channel code such as Turbo code or LDPC code which shows a performance close to the Shannon`s limit is employed. The noise model of Wyner-Ziv coding for channel decoding is called Virtual Channel Noise and is generally modeled by Laplacian or Gaussian distribution. In this paper, we propose a Wyner-Ziv coding method based on the frequency-adaptive channel noise modeling in transform domain. The experimental results with various sequences prove that the proposed method makes the channel noise model more accurate compared to the conventional scheme, resulting in improvement of the rate-distortion performance by up to 0.52dB.

Traditional broadcasting environment is merged with various interactive broadcasting services, and the users use these services through Set-Top-Boxes. But they have limited user interfaces, which are not suitable for TV environments by adopting internet formats. Therefore, this paper suggests a User Navigating Interface which helps the audiences to select and watch their favorite channels more effectively. Firstly, this paper analyzes EPG interface - the most basic service in interactive broadcasting. Secondly, it suggests a user interface and service structure suitable in the network-integrated TV environment.

The DIBR(depth image-based rendering) method gives the sense of depth to viewers by using one color image and corresponding depth image. At this time, the qualities of the generated left- and right-image depend on the baseline distance of the virtual cameras corresponding to the view of the generated left- and right-image. In this paper, we present a novel method for enhancing the sense of depth by adjusting baseline distance of virtual cameras. Geometric analysis shows that the sense of depth is better in accordance with the increasing disparity due to the reduction of the image distortion. However, the entailed image degradation is not considered. Experimental results show that there is maximum bound in the disparity increasement due to image degradation and the visual field. Since the image degradation is reduced for increasing that bound, we add a depth map preprocessing. Since the interactive service where the disparity and view position are controlled by viewers can also be provided, the proposed method can be applied to the mobile broadcasting system such as DMB as well as 3DTV system.

In this paper, we propose the method which provides efficient sub-channel allocation for handoff and new call supporting multi-media service in AMC-based OFDMA system. Firstly, we apply the multi-band method which provides different AMC method according to the location of user terminals. Also, in OFDMA system environment that a base station has a lot of sub-channels, we adopt the sub-channel allocation scheme that provides a higher priority to handoff call and real-time service about handoff and new calls with multi-meida service. The simulation results show that the proposed scheme plays a role in increasing the number of new and handoff calls meeting the required blocking rate.

We propose a hybrid broadcast scheduling based on a combination of periodic and on-demand data scheduling methods for mobile data broadcasting in convergence networks from communication and broadcasting. We consider an environment in which the forward channel is for data broadcasting and the reverse channel is for sending data requests via cellular phones, WLAN, WiBro, etc. Collecting statistics of requests from clients, the server partitions the data items into hot-item and cold-item sets. Hot items are sent based on a push-based scheduling. An on-demand scheduling method is applied to cold items. Performance evaluation from simulations shows that our proposed scheduling algorithm yields small response time with high successful response ratio.

Stereoscopic video delivers depth perception to users contrary to 2D video. Therefore, we need to develop a new video quality assessment model for stereoscopic video. In this paper, we propose a new method for objective assessment of stereoscopic video. The proposed method detects blocking artifacts and degradation in edge regions such as in conventional video quality assessment model. And it detects video quality difference between views using depth information for efficient quality prediction. We performed subjective assessment of stereoscopic video to check the performance of the proposed method, and we confirmed that the proposed algorithm is superior to the existing method in PSNR in respect to correlation with results of the subjective assessment.

The 3D shape as well as the depth of an object presented on a 3D display is perceptually distorted depending on viewing distance. It is quite undesirable that different observers perceive different depth and shape from an object displayed on a 3D monitor. To resolve the problem of perceptual distortion of 3D depth and shape, the degree of the distortion should be measured appropriately. As a basis for resolving these problems, the present research suggests an instrument for measuring the degree of the perceptual distortion of 3D depth and shape.

In H.264/AVC, if each block is quantized with a adaptive quantization parameter(QP) regardless of the characteristics of a block, it could be the deterioration of the picture quality. In this paper, an adaptive block-based QP selection method is proposed in order to improve picture quality by utilizing the bit amounts of the zigzag-scanned integer transform coefficients of the neighboring blocks and changing the QP value in the current block. The proposed method works in the same way as the encoder and decoder without transmitting the change of QP value to the decoder side. The experimental results show that the proposed method achieves a gain of about compared with H.264/AVC.

This paper examines the potential of Ultra-High Definition TV (UD-TV) broadcasting transmission systems beyond HD-TV over cable channel. Firstly, we analyze the trend of TOV(Threshold of Visibility) by extending the OpenCable (J.83 Annex B) system 256QAM which is the standard of Korean and American cable television transmission to 1024QAM, and realize that the OpenCable 1024QAM has nearly 30% higher data rate than 256QAM at the expense of impractically higher TOV (Threshold of Visibility). To achieve practical TOV, we control code rates of inner convolutional coder and replace turbo coder in forward error correction (FEC) part, thereby analyzing the best performance of the OpenCable systems having conventional FEC. In that result, it is necessary to modify conventional FEC of the OpenCable system to achieve under 31.5dB TOV. Moreover we study the potential of UD-TV transmission via two or more TV channels, so called channel bonding, through the Shannon capacity in 6MHz channel and the relationship with next generation A/V codec technologies.

Due to the rapid increase of available contents via the convergence of broadcasting and internet, the efficient access to personally preferred contents has become an important issue. In this paper, for recommendation scheme for TV programs using a collaborative filtering technique is studied. For recommendation of user preferred TV programs, our proposed recommendation scheme consists of offline and online computation. About offline computation, we propose reasoning implicitly each user`s preference in TV programs in terms of program contents, genres and channels, and propose clustering users based on each user`s preferences in terms of genres and channels by dynamic fuzzy clustering method. After an active user logs in, to recommend TV programs to the user with high accuracy, the online computation includes pulling similar users to an active user by similarity measure based on the standard preference list of active user and filtering-out of the watched TV programs of the similar users, which do not exist in EPG and ranking of the remaining TV programs by proposed rank model. Especially, in this paper, the BM (Best Match) algorithm is extended to make the recommended TV programs be ranked by taking into account user`s preferences. The experimental results show that the proposed scheme with the extended BM model yields 62.1% of prediction accuracy in top five recommendations for the TV watching history of 2,441 people.

This paper presents an algorithm, aims at practical applications, for the high speed processing and performance enhancement of lane detection base on vision processing system. As a preprocessing for high speed lane detection, the vanishing line estimation and the optimal extraction of region of interest for lane boundary (ROI-LB) can be processed to reduction of detection region in which high speed processing is enabled. Image feature information is extracted only in the ROI-LB. Road lane is extracted using a non-parametric model fitting and Hough transform within the ROI-LB. With simultaneous processing of noise reduction and edge enhancement using the Laplacian filter, the reliability of feature extraction can be increased for various road lane patterns. Since outliers of edge at each block can be removed with clustering of edge orientation for each block within the ROI-LB, the performance of lane detection can be greatly improved. The various real road experimental results are presented to evaluate the effectiveness of the proposed method.