Currently deployed mobile networks including High Speed Downlink Packet Access (HSDPA) offer only best-effort Quality of Service (QoS). In wireless best effort networks, the bandwidth variation is a critical problem, especially, for mobile devices with small buffers. This is because the bandwidth variation leads to packet losses caused by buffer overflow as well as picture freezing due to high transmission delay or buffer underflow. In this paper, in order to provide seamless video streaming over HSDPA, we propose an efficient real-time video streaming method that consists of the available bandwidth (AB) estimation for the HSDPA network and the transmission rate control to prevent buffer overflows/underflows. In the proposed method, the client estimates the AB and the estimated AB is fed back to the server through real-time transport control protocol (RTCP) packets. Then, the server adaptively adjusts the transmission rate according to the estimated AB and the buffer state obtained from the RTCP feedback information. Experimental results show that the proposed method achieves seamless video streaming over the HSDPA network providing higher video quality and lower transmission delay.

Video transmission over mobile worldwide interoperability for microwave access (WiMAX) can be serverly degraded due to the effect of fading and handoff. In this paper, we propose a channel adaptive error resilience scheme for video transmission over mobile WiMAX. When the channel condition begins to trigger handoff, the current frame is stored in the long-term memory for the forward error correction, and the following frames are encoded by using double motion vectors (MVs) in the sense of multi-hypothesis motion compensation. Even if a whole frame is lost, we can reconstruct the following frames using the stored frame in the long-term memory. However, the error propagation still remains in this forward error resilience method. To refresh the erroneous frames to the decoder, the encoder utilizes the channel adaptive refreshing (CAR). In the CAR, the channel rate is first predicted using channel parameter, a carrier to interference and noise ratio (CINR), and the encoder adaptively determines the number of blocks to be encoded in the intra mode based on the feedback information. Performance evaluations are presented to demonstrate the effectiveness of the proposed method.

Context-based Adaptive Binary Arithmetic Coding (CA-BAC) is adopted as an entropy coding tool for main profile of the video coding standard H.264/AVC. CABAC achieves higher degree of redundancy reduction by estimating the conditional probability of each binary symbol which is the input to the arithmetic coder. This paper presents an entropy coding method based on CABAC. In the proposed method, the binary symbol is coded using more precisely estimated conditional probability, thereby leading to performance improvement. We apply our method to the standard and evaluate its performance for different video sources and various quantization parameters (QP). Experiment results show that our method outperforms the original CABAC in term of coding efficiency, and the average bit-rate savings are up to 1.2%.

Video quality generally suffers from packet losses caused by an unreliable channel when video is transmitted over an error-prone wireless channel. This quality degradation is the main reason that a video compression encoder uses error-resilient coding to deal with the high packet-loss probability. The use of adequate error resilience can mitigate the effects of channel errors, but the coding efficiency for bit reduction will be decreased. On the other hand, H.264/AVC uses multiple reference frame (MRF) motion compensation for a higher coding efficiency. However, an increase in the number of reference frames in the H.264/AVC encoder has been recently observed, making the received video quality worse in the presence of transmission errors if the cyclic intra-refresh is used as the error-resilience method. This is because the reference-block selection in the MRF chooses blocks on the basis of the rate distortion optimization, irrespective of the intra-refresh coding. In this paper, a new error-resilient reference selection method is proposed to provide error resilience for MRF based motion compensation. The proposed error-resilient reference selection method achieves an average PSNR enhancement up to 0.5 to 2dB in 10% packet-loss-ratio environments. Therefore, the proposed method can be valuable in most MRF-based interactive video encoding system, which can be used for video broadcasting and mobile video conferencing over an erroneous network.

Error concealment at a decoder is an efficient method to reduce the degradation of visual quality caused by channel errors. In this paper, we propose a novel spatio-temporal error concealment algorithm based on the spatial-temporal fading (STF) scheme which has been recently introduced. Although STF achieves good performance for the error concealment, several drawbacks including blurring still remain in the concealed blocks. To alleviate these drawbacks, in the proposed method, hybrid approaches with adaptive weights are proposed. First, the boundary matching algorithm and the decoder motion vector estimation which are well-known temporal error concealment methods are adaptively combined to compensate for the defect of each other. Then, an edge preserved method is utilized to reduce the blurring effects caused by the bilinear interpolation for spatial error concealment. Finally, two concealed results obtained by the hybrid spatial and temporal error concealment are pixel-wisely blended with adaptive weights. Experimental results exhibit that the proposed method outperforms conventional methods including STF in terms of the PSNR performance as well as subjective visual quality, and the computational complexity of the proposed method is similar to that of STF.