We present a hybrid scalable video coding algorithm in which two types of scalabilities, i.e., layered scalability and parallel scalability, are combined to achieve higher order of flexibility for heterogeneous networks and mixed client requirements. In space domain, SNR scalable video coding is used to give layered scalability on frame quality; while in temporal domain, a multiple description approach, the Multiple State Video Coding (MSVC), provides parallel scalability to the base layer video. Two coarsely quantized sub-streams are yielded using MSVC and form the base layer. All residual signals of the video sequence are coded into a third sub-stream and form the enhancement layer. The hybrid scalable video protects the base layer using multiple description and has better performance than conventional layered scalable video when a base layer picture is damaged. It gives similar performance as SNR scalable video when the enhancement layer encounters errors. In general packet drop networks, the proposed scalable video achieves higher PSNR than the original MSVC video and single description video in high packet drop rate environments.
Error resilience becomes an important feature of video applications over networks. Due to widely used motion-compensated prediction coding, an important method to combat or conceal errors is providing robust prediction reference. If each block uses one reference, the situation is not different from conventional prediction. If multiple references are used, cost of motion search will increase dramatically.
To take advantage of both low complexity of using one reference and robustness of using multiple references, we proposed a video coding system that composes a virtual frame based on previously decoded frames and use it as a prediction reference. The frame is generated by applying a nonlinear filter on previously coded frames. In error free environment, both encoder and decoder can compose an identical reference frame. In case of error, the decoder first conceals the errors by predicting the damaged blocks spatially. Effect of errors is further constrained by composing a reference frame since correct data from decoded frames are used. Lower video quality degradation and smaller quality oscillation can be achieved. Since the composed reference may have lower correlation with the current frame and damage some details, coding efficiency will slightly decrease.
This paper proposes a modified Fixed-length Entropy Coding(FLC) algorithm suitable for MPEG-like hybrid-based video compression. In such applications, the alphabets of symbols sending to entropy coding are of heavy-tail distributions. Previously proposed algorithms either have poor compression efficiency or are computationally complex in this situation. The technique proposed in this paper extends the previous work for the important case of large alphabets by introducing a new alphabet segmentation and splitting algorithm. Simulation results show that for sources with relative large, skewed and heavy-tail distributed alphabets, the proposed approach has faster alphabet shrinking and higher compression efficiency compared with previous FLC approaches. A hybrid video codec using the proposed FLC is implemented and compared to a MPEG-2 video codec in both noise-free and noisy environments. The results demonstrate that the proposed FLC has similar compression gain as common VLC, and FLC codes provide more robustness to video streams than VLC codes. The proposed technique can be used to compress video sequences transmitted over channels with random bit errors.