For compressed sensing, to address problems which do not involve reconstruction, a correlation analysis between measurements and the transform coefficients is proposed. It is shown that there is a linear relationship between them, which indicates that we can abstract the inner property of images directly in the measurement domain.

This paper proposes a statistical expression of the output error variance due to coefficient quantization in separable denominator M-D digital filters. Using this expression, this paper shows that minimization of overall quantization errors can be performed by minimizing the roundoff noise.

An adaptive selective retransmission algorithm for video communications based on packet importance value is proposed. The algorithm can adaptively select the retransmission threshold in realtime and efficiently manage the retransmission process in heavy loaded networks while guaranteeing acceptable video quality at the receiver.

A new selective retransmission method for HARQ (Hybrid Automatic Repeat reQuest) systems is proposed. This method can avoid the blindness of symbols retransmission by the transformation of lostmap matrix and simulation results show that the proposed method can reduce the number of retransmissions effectively.

Based on an estimation model of video subjective quality, a bandwidth reallocation strategy for video communications on NGN is presented. Experimental results show that the average PSNR of recovery video quality can be greatly increased by using the proposed method when the network bandwidth decreases.

Distributed compressed video sensing (DCVS), combining advantages of compressed sensing and distributed video coding, is developed as a novel and powerful system to get an encoder with low complexity. Nevertheless, it is still unclear how to explore the method to achieve an effective video recovery through utilizing realistic signal characteristics as much as possible. Based on this, we present a novel spatiotemporal dictionary learning (DL) based reconstruction method for DCVS, where both the DL model and the l1-analysis based recovery with correlation constraints are included in the minimization problem to achieve the joint optimization of sparse representation and signal reconstruction. Besides, an alternating direction method with multipliers (ADMM) based numerical algorithm is outlined for solving the underlying optimization problem. Simulation results demonstrate that the proposed method outperforms other methods, with 0.03-4.14 dB increases in PSNR and a 0.13-15.31 dB gain for non-key frames.

An intra refresh matrix, which models the importance of each macroblock, is first created. This matrix can be used to decide the coding mode of the macroblocks. The proposed technique can greatly improve the decoded video quality over the variable and error-prone channel with high packet loss rate.

A direct inter-mode selection algorithm for P-frames in fast homogeneous H.264/AVC bit-rate reduction transcoding is proposed in this paper. To achieve the direct inter-mode selection, we firstly develop a low-complexity distortion estimation method for fast transcoding, in which the distortion is directly calculated from the decoded residual together with the reference frames. We also present a linear estimation method to approximate the coding rate. With the estimated distortion and rate, the rate-distortion cost can be easily computed in the transcoder. In our algorithm, a method based on the normalized rate difference of P-frames (RP) is used to detect the high motion scene. To achieve fast transcoding, only for the P-frames with RP larger than a threshold, the rate-distortion optimized (RDO) mode decision is performed; meanwhile, the average cost of each inter-mode (ACM) is calculated. Then for the subsequent frames transcoding, the optimal coding mode can be directly selected using the estimated cost and the ACM threshold. Experiments show that the proposed method can significantly simplify the complex RDO mode decision, and achieve transcoding time reductions of up to 62% with small loss of rate-distortion performance.