This paper provides a technical overview of a newly added in-loop filtering technique, sample adaptive offset (SAO), in High Efficiency Video Coding (HEVC). The key idea of SAO is to reduce sample distortion by first classifying reconstructed samples into different categories, obtaining an offset for each category, and then adding the offset to each sample of the category. The offset of each category is properly calculated at the encoder and explicitly signaled to the decoder for reducing sample distortion effectively, while the classification of each sample is performed at both the encoder and the decoder for saving side information significantly. To achieve low latency of only one coding tree unit (CTU), a CTU-based syntax design is specified to adapt SAO parameters for each CTU. A CTU-based optimization algorithm can be used to derive SAO parameters of each CTU, and the SAO parameters of the CTU are inter leaved into the slice data. It is reported that SAO achieves on average 3.5% BD-rate reduction and up to 23.5% BD-rate reduction with less than 1% encoding time increase and about 2.5% decoding time increase under common test conditions of HEVC reference software version 8.0.

A new video coding tool, sample adaptive offset (SAO), is introduced in this paper. SAO has been adopted into the Working Draft of the new video coding standard, High-Efficiency Video Coding (HEVC). The SAO is located after deblocking in the video coding loop. The concept of SAO is to classify reconstructed pixels into different categories and then reduce the distortion by simply adding an offset for each category of pixels. The pixel intensity and edge properties are used for pixel classification. To further improve the coding efficiency, a picture can be divided into regions for localization of offset parameters. Simulation results show that SAO can achieve on average 2% bit rate reduction and up to 6% bit rate reduction. The run time increases for encoders and decoders are only 2%.

In this paper, a one-pass encoding algorithm is proposed for adaptive loop filter (ALF) in high-efficiency video coding (HEVC). ALF can improve both subjective and objective video quality, but it also requires a lot of encoding passes (i.e. picture buffer accesses) that will significantly increase external memory access, encoding latency, and power consumption. Therefore, we propose a method to estimate filtering distortion without performing real filter operation. The number of encoding passes can be effectively reduced from 16 to 1. Combined with an initial guess of filter-on/off blocks by using time-delayed filters, the proposed one-pass algorithm only induces average 0.17% BD-rate increase.

Adaptive interpolation filtering (AIF) algorithms have been proposed to enhance the hybrid video coding scheme recently. Although these algorithms can improve coding efficiency significantly, their encoders suffer huge increase in complexity in terms of latency and memory access due to its inherent multi-pass encoding procedure. In this paper, we present a novel single-pass solution for these algorithms, which allows optimal selection among different interpolation filters. In this solution, time-delayed interpolation filters are used to achieve single-pass encoding, and localized ratedistortion (RD) selection is used to compensate the possible coding loss from time-delayed filters. Experimental results show that the proposed method is efficient for All AIF techniques in current ITU-T/SG16 reference software. By using the proposed method, single-pass encoding with multiple AIF filters can be achieved while maintaining similar coding efficiency as multi-pass AIF.

This paper proposes a novel multi-class hybrid-boost learning algorithm for multi-pose face detection and facial expression recognition. This system detects human face in different sizes, various poses, partial-occlusion, and different expressions. The contribution of this paper is the hybrid boosting algorithm combining the Haar-like (local) features and Gabor-like (global) features. The experimental results show that our system has better performance than the others.

This paper presents a real-time pointing arm tracking and identification system. It uses three cameras to track the pointing arm and identifies the pointed targets in 3-D space. The user make the arm pointing gesture at anyplace in the working space. Our system uses particle filtering and direct linear transformation (DLT) to track two 3-D points on the pointing arm and applies the epipolar geometry to refine the tracking results. In the experiments, we demonstrate that the hit rate is above 90%.

We propose a subspace-based maximum-likelihood approach for acquiring the timing of wavelet-based multirate transmission systems. The S-curve analysis shows that our approach can correctly acquire the initial timing of a symbol from anywhere within a symbol-time interval at a cost of increasing jitter variance.

We propose a new framework for multiple scalable bitstream video communications over lossy channels. The major feature of the framework is that the encoder estimates the effects of postprocessing concealment and includes those effects in the rate-distortion analysis. Based on the framework, we develop a rate-distortion optimization algorithm to generate multiple scalable bitstreams. The algorithm maximizes the expected peak signal-to-noise ratio by optimally assigning forward error control codes and transmission schemes in a constrained bandwidth. The framework is a general approach motivated by previous methods that perform concealment in the decoder, as in our special case. Simulations show that the proposed approach can be implemented efficiently and that it outperforms previous methods by more than 2 dB.

We propose an error control scheme for video communications over lossy channels. The proposed algorithm uses receiver post-processing in analysis to coordinate with multiple encoded streams which is capable of handling error concealment and error protection to achieve robust transmissions. Unlike previous methods, our algorithm focuses on joint optimizing multiple substreams distortion with concealment over error prone channels. The algorithm minimizes the expected rate-distortion function to achieve the optimal FEC result. In the experiments, we demonstrate the effectiveness of our method by using a 3-D SPIHT algorithm. Simulation results show that the proposed protection strategy achieves about 2 dB higher peak signal-to-noise ratio compared to conventional method.

In this paper, we propose an error control scheme for video communications over lossy channels. The proposed algorithm uses error concealment protection (ECP) approach to coordinate with multiple encoded streams which is capable of handling error concealment to achieve robust transmissions. Unlike previous methods, our algorithm focuses on joint optimizing multiple substreams distortion with concealment over error prone channels. The algorithm minimizes the expected rate-distortion function to achieve the optimal FEC result. In the experiments, we demonstrate the effectiveness of our method by using a 3-D SPIHT algorithm. Simulation results show that the proposed protection strategy achieves about 2 dB higher peak signal-to-noise ratio compared to conventional method.

We propose an efficient error-resilient video transmission algorithm over packet erasure channels using optimal source and channel bit-allocation. This algorithm uses FEC and rate-distortion optimization to find the optimal allocation of source and channel bits in each quality layer. The packet loss probability is periodically reported to the video server. This method can also be incorporated with any coding structure that generates a set of independent compressed bitstreams. The algorithm efficacy is demonstrated by simulations in which the video compression is an error-resilient 3D-SPIHT algorithm and the channel protection is provided by Reed-Solomon (RS) codes.

This paper proposes a new error resilient video coding scheme using the matching pursuit (MP) residual coding and the multiple description coding. A conventional discrete cosine transform-based video coding scheme introduces undesirable blocking artifacts at low bit rates. MPs for residual coding has been developed to overcome the disadvantage. The parameters obtained after MP, called atoms, are encoded into two balanced descriptions using scalar quantizers. The two descriptions are respectively transmitted over two separate channels. If both descriptions are received, a high-quality reconstruction can be obtained, however, if either description is lost, a low-quality, but acceptable, reconstruction can be acquired.

We propose a clock acquisition algorithm for timing recovery for fractal modulation in additive white Gaussian noise (AWGN) and 1/f channels. Our acquisition algorithm uses exclusively the data redundancy inherently built in the fractal modulation to locate the beginning of timing of all the subbands simultaneously. Different diversity techniques can then be applied after the beginning of the data block is obtained. Our acquisition functions are derived by using the maximum-likelihood method. Using a serial search algorithm to maximize the acquisition function, we may find the timing point. Simulations have been conducted in evaluating the mean acquisition time of our algorithm.

The acquisition problem in wavelet-based modulation is very important. We discuss the problem of the ML-based method proposed by M. Luise et al. (see IEEE Trans. Commun., vol.48, p.1047-54, 2000) for timing acquisition and then we develop a novel acquisition algorithm. Our method uses the properties of the scaling function in the derivation of the acquisition function. We also show that the S-curve of our acquisition algorithm is smooth and has a unique zero during the signaling interval. Thus, we can acquire the correct symbol timing without ambiguity. The performance of our acquisition algorithm is evaluated by Monto-Carlo simulation using the Meyer wavelet.

We propose a naive algorithm for the timing recovery for fractal modulation. We first investigate the bit error rate due to the clock error of a fractal modulation. Then, we propose clock synchronization techniques for fractal modulation. Our acquisition algorithm uses exclusively the self-similar property of fractal for signal modulation. The performance of our algorithm is also demonstrated.