Rhandley Domingo Cajote

FMO slice group maps using spatial and temporal indicators for H.264 wireless video transmission

We present a new method, the STI-FMO, that combines spatial and temporal indicators of MB importance to generate slice group maps for H.264 wireless video transmission. Starting from an initial MB-to-slice group mapping we propose a distortion-from-propagation measure that can be used to generate a slice group map that offers less distortion than the initial map from an error concealment point of view. The new method exploits the location of the MB within a slice group, the distortion measure of the MB in the same slice and the probability of error of a MB estimated from the bit-count information to compute a distortion-from-propagation measure. The new method considers the effect of the MBs location within a slice group as added information to assess its importance. Experiments indicate the effectiveness of the proposed method.

Normalized adaptive minimum bit-error-rate beamformers

We address the convergence limitations of adaptive minimum bit-error-rate beamformers (AMBER) beamformers under fading channel environments by developing the normalized AMBER (NAMBER) beamforming algorithms. NAMBER beamformers make use of probability-of-bit-error cost functions that are normalized vs. input signal level. The NAMBER beamformers include the normalized MBER (NMBER), normalized block-adaptive-MBER (NBAMBER), normalized least-bit-err or-rate (NLBER) and normalized approximate least-bit-error-rate (NALBER). Simulation results show that the NMBER can achieve lower BERs compared to MBER and maximum-signal-to-interference-plus noise ratio (MSINR) under a fading channel environment.

Global word shape processing using polar-radii graphs for offline handwriting recognition

The result of investigating the capability of the polar-radii graph (PRG) of the word contour as a global feature for offline handwriting recognition is presented in this paper. The PRG is combined with the local geometric features to improve the accuracy of the handwriting recognition system. The handwriting recognition system using local features and an HMM recognizer obtained a recognition rate of 58% for a 20-word vocabulary using the demo version of the publicly available IAM database. Using the PRG of the word contour as a global feature and an MLP classifier, the recognition rate is 78%. Using the linear confidence accumulation (LCA) method to combine the results of the recognizers based on the local and global features, an over-all recognition accuracy of 72% was obtained.

Joint explicit FMO, FEC coding, and adaptive interleaving depth for H.264 wireless video transmission

Flexible macroblock ordering (FMO) is an error resilience tools in H.264 that can be used to mitigate errors in video transmission and is shown to be effective in the previous research findings. In this paper, the effectiveness of integrating explicit map using bit-count FMO, i.e., a macroblock level interleaving, with Forward Error Correction (FEC) coding and interleaving, i.e., bit-level interleaving, has been investigated. To cope with burst errors in various fading conditions, we proposed to adaptively adjust interleaving depth based on the mean burst length statistics obtained the previous frames. Based on the channel condition prediction, FMO is only used when the channel condition is good. Alternatively FMO with FEC and adaptive interleaving depth is used when the channel condition is bad. The simulation results under slow and fast fading wireless channel scenarios show that our proposed scheme help reduce the number of undecodable macroblock of up to 88% and achieve the PSNR improvement of up to 7.5 dB, compared to not using error mitigation scheme. Thus, the proposed framework could be adopted as error mitigation scheme for wireless video transmission.

FMO-based H.264 frame layer rate control for low bit rate video transmission

The use of flexible macroblock ordering (FMO) in H.264/AVC improves error resiliency at the expense of reduced coding efficiency with added overhead bits for slice headers and signalling. The trade-off is most severe at low bit rates, where header bits occupy a significant portion of the total bit budget. To better manage the rate and improve coding efficiency, we propose enhancements to the H.264/AVC frame layer rate control, which take into consideration the effects of using FMO for video transmission. In this article, we propose a new header bits model, an enhanced frame complexity measure, a bit allocation and a quantization parameter adjustment scheme. Simulation results show that the proposed improvements achieve better visual quality compared with the JM 9.2 frame layer rate control with FMO enabled using a different number of slice groups. Using FMO as an error resilient tool with better rate management is suitable in applications that have limited bandwidth and in error prone environments such as video transmission for mobile terminals.

Improved Sorting Algorithm for Explicit FMO Macroblock Classification in H.264

An improved sorting algorithm is presented that classifies macroblocks into different slice groups for FMO in H.264. The classification process reinforces the slice structured coding nature of H.264 by making a conscious effort to minimize the variations in the statistics of the macroblock parameters of the resulting slice group maps. Results show that modest improvements can be achieved in terms of PSNR and the number of undecodable macroblocks by using the proposed improved sorting algorithm as compared to an interleave sorting algorithm where the MB is assigned to different slice groups following the order of the sorted list.

Framework of surveillance video analysis and transmission system using background modeling and MIMO-OFDM

In this paper, a new video analysis and background modeling suitable for wireless video surveillance networks is proposed. Using video analysis, the proposed system can detect any location of important information from the video data, e.g., the location of persons, and then the whole video data can be drastically reduced by using background modeling except the above detected important information. In our experimental system, Motion JPEG video compression and 2×2-MIMO-OFDM wireless are used into a base system. The system can reduce of up to 87.41% of the video data using the proposed method with average PSNR of 25.92 dB using SD resolution image, with comparable image quality when background modeling is not used. Using HD resolution video simulations shows that the proposed schemes achieves slightly better PSNR performance.

Low complexity adaptive intra-refresh rate for real-time wireless video transmission

Real-time wireless video transmission systems must consider both error resiliency and low complexity. However, most error resilient features of recent video coding standards tend to increase computational complexity of the encoder. In this paper, we propose a low complexity error resilient joint source-channel adaptive intra-refresh rate scheme where the optimum number of intra-coded macroblocks is determined at frame level based on the minimum estimated end-to-end distortion. In this work, we propose source and transmission distortion models whose parameters are independent on sequence type which allows real-time video encoding. The source distortion model is based on residual information and quantization step using linear least square method. The residual information is estimated using the mean-absolute difference (MAD) prediction model based on the linear relationship between intra-refresh rate and MAD. The transmission distortion model is based on recursive model using reliable feedback channel. The proposed models are used to implement a joint source-channel video coding scheme using standard H.264/AVC encoder. Accurate estimate of the actual distortion at various refresh rates are achieved and able to estimate the distortion before encoding the frame. The proposed scheme is compared with random and periodic intra refresh schemes under wireless fading channel. Improvements in PSNR quality are measured which verifies the effectiveness of the proposed scheme especially in time varying channel conditions.

Physical layer implementation of orthogonal frequency division multiplexing for software defined radio on FPGA

This paper discusses the implementation of a software defined radio (SDR) that uses orthogonal frequency division multiplexing (OFDM). The transmitter and receiver were modeled and simulated using the Xilinx® blockset in MATLAB Simulink® then implemented on hardware using Xilinx® System Generator. Performance of the SDR system was evaluated by measuring BER, PAPR and spectral efficiency under simulated channel conditions with SNR of 15 and 20 dB. For speech inputs, 8-FFT 16ASK and 16-FFT 64ASK are acceptable for SNR of 15 and 20 dB, respectively. For audio inputs, 8-FFT PSK and 8-FFT 16ASK are acceptable. These were based on a minimum BER of 10-2 for speech and 10-3 for audio inputs. The chosen configurations were implemented on a Xilinx® Virtex-5 FPGA built in the XtremeDSP™ Development Platform ML506 Edition using JTAG hardware co-simulation. The BER performance of the system on hardware was consistent with that observed in simulations using fixed-point computations.

Improvement on error concealment for H.264 spatial scalable video coding

One of the scalability features in H.264/SVC is spatial scalability, and it is found to be useful in distribution of video content to a variety of consumers. Transmission of an H.264/SVC stream over a packet network may introduce losses, at worst case would involve whole frame losses. It is necessary to conceal the errors in the decoded bitstream. We propose an improvement in the error concealment scheme in H.264/SVC by improved motion estimation and post processing of the concealed frames in the pixel domain. The proposed method successfully conceals the lost frame and was found to be effective for low bitrate video transmission over conventional methods.