Error Resilient Transcoding Research Articles

Error Resilient Video Transcoding Based on Layered Rate Distortion Optimization

Error resilient video transcoding can insert error resilient tools in the compressed video to enhance error resilience of the video over wireless channels. However the error resilience insertion increases bit rate while reducing distortion. So the rate distortion optimization is required. In order to solve this problem,this paper proposes an error resilient video transcoding algorithm based on layered rate distortion optimization. This algorithm improves the flexibility by performing rate distortion optimization with different granularity for synchronization marker insertion and intra macroblock refresh on the frame layer and macroblock layer respectively. Moreover this algorithm improves the accuracy by accounting for the intra refresh,intra prediction,motion vector prediction on the frame layer and reduces the complexity by reducing the candidate macroblock modes on the macroblock layer. The simulation results show that the proposed algorithm improves PSNR by 0.6~1.1dB and reduces the complexity by about 25% compared with the algorithms based on single layer rate distortion optimization.

Compressed-Domain Techniques for Error-Resilient Video Transcoding Using RPS

In video applications where video sequences are compressed and stored in a storage device for future delivery, the encoding process is typically carried out without enough prior knowledge about the channel characteristics of a network. Error-resilient transcoding plays an important role to provide an addition of resilience to the video data, where or whenever it is needed. Recently, a reference picture selection (RPS) scheme has been adopted in an error-resilient transcoder in order to reduce error effects for the already encoded video bitstream. In this approach, the transcoder learns through a feedback channel about the damaged parts of a previously coded frame and then decides to code the next P-frame not relative to the most recent, but to an older, reference picture, which is known to be error-free in the decoder. One straightforward approach of adopting RPS in error-resilient transcoding is to decode all the P-frames from the previously nearest I-frame to the current transmitted frame which is then re-encoded with a new reference frame; this can create undesirable complexity in the transcoder as well as introduce re-encoding errors. In this paper, some novel techniques are suggested for an effective implementation of RPS in the error-resilient transcoder with the minimum requirement on its complexity. All the proposed techniques will manipulate video data in the compressed domain such that the computational loading of the transcoder is greatly reduced. By utilizing these new compressed-domain techniques, we develop a new structure to handle various types of macroblocks in the transcoder which re-uses motion vectors and prediction errors from the encoded bitstream. Experimental results demonstrate that significant improvements in terms of transcoder complexity and quality of reconstructed video can be achieved by employing our compressed-domain techniques.

Intra/Inter Macroblock Mode Decision for Error-Resilient Transcoding

When transmitting the precoded bitstream over an error-prone network, error-resilient transcoding is adopted to convert the bitstream to a resilient format for robust delivery. Intra refreshment is an efficient tool to reduce the dependency between frames and stop the channel error propagation. In the conventional scheme, the rate-distortion optimized macroblock mode decision is employed to adaptively determine the coding mode of each macroblock. However, this scheme only considers the channel error propagated from the previous frames to the current frame. As opposed to this traditional algorithm, this paper proposes a method which considers consecutive two frames in a sequence, thus taking the error propagation to the following frame into account. This enhances the overall robustness of the transcoded bitstream against the packet loss. Considering the availability of the next frame information, two cases are discussed respectively. Experimental results show that the proposed methods present quality improvement when compared with the conventional rate-distortion optimized error-resilient coding scheme under different test environments, and the PSNR improvement can reach as high as 0.9 dB.

Video transcoding architectures and techniques: an overview

Throughout this article, we concentrate on the transcoding of block-based video coding schemes that use hybrid discrete cosine transform (DCT) and motion compensation (MC). In such schemes, the frames of the video sequence are divided into macroblocks (MBs), where each MB typically consists of a luminance block (e.g., of size 16 /spl times/ 16, or alternatively, four 8 /spl times/ 8 blocks) along with corresponding chrominance blocks (e.g., 8 /spl times/ 8 Cb and 8 /spl times/ 8 Cr). This article emphasizes the processing that is done on the luminance components of the video. In general, the chrominance components can be handled similarly and will not be discussed in this article. We first provide an overview of the techniques used for bit-rate reduction and the corresponding architectures that have been proposed. Then, we describe the advances regarding spatial and temporal resolution reduction techniques and architectures. Additionally, an overview of error resilient transcoding is also provided, as well as a discussion of scalable coding techniques and how they relate to video transcoding. Finally, the article ends with concluding remarks, including pointers to other works on video transcoding that have not been covered in this article, as well as some future directions.

Error-resilient transcoding for video over wireless channels

We describe a method to maintain quality for video transported over wireless channels. The method is built on three fundamental blocks. First, we use a transcoder that injects spatial and temporal resilience into an encoded bitstream. The amount of resilience is tailored to the content of the video and the prevailing error conditions, as characterized by bit error rate. Second, we derive analytical models that characterize how corruption propagates in a video that is compressed using motion-compensated encoding and subjected to bit errors. Third, we use rate distortion theory to compute the optimal allocation of bit rate among spatial resilience, temporal resilience, and source rate. Furthermore, we use the analytical models to generate the resilience rate distortion functions that are used to compute the optimal resilience. The transcoder then injects this optimal resilience into the bitstream. Simulation results show that using a transcoder to optimally adjust the resilience improves video quality in the presence of errors while maintaining the same input bit rate.