Transform Domain Wyner-Ziv Video Codec Research Articles

Efficient Motion Field Interpolation Method for Wyner-Ziv Video Coding

Wyner-Ziv video coding has the capability to reduce video encoding complexity by shifting motion estimation procedure from encoder to decoder. Amongst many motion estimation methods, e xpectation m aximization algorithm is the most effective one. Unfortunately, the implementation of block-based motion estimation in this algorithm causes motion field profile bounded by granularity of block size. Nearest-neighbor and bilinear interpolation methods have already applied in multiview image coding to handle similar problem. This paper aims to evaluate performance of both interpolation methods in transform-domain Wyner-Ziv video codec. Results showed that bilinear interpolation effective only for high motion video sequences. In this scenario, it has bitrate saving up to 3.29 %, 0.2 dB higher PSNR, and 12.30 % higher decoding complexity compared to nearest-neighbor. In low motion video content, bitrate saving only gained up to 0.82%, with almost the same PSNR, while decoding complexity increase up to 10.32%.

Adaptive deblocking filter for transform domain Wyner–Ziv video coding

Wyner-Ziv (WZ) video coding is a particular case of distributed video coding, the recent video coding paradigm based on the Slepian-Wolf and Wyner-Ziv theorems that exploits the source correlation at the decoder and not at the encoder as in predictive video coding. Although many improvements have been done over the last years, the performance of the state-of-the-art WZ video codecs still did not reach the performance of state-of-the-art predictive video codecs, especially for high and complex motion video content. This is also true in terms of subjective image quality mainly because of a considerable amount of blocking artefacts present in the decoded WZ video frames. This paper proposes an adaptive deblocking filter to improve both the subjective and objective qualities of the WZ frames in a transform domain WZ video codec. The proposed filter is an adaptation of the advanced deblocking filter defined in the H.264/AVC (advanced video coding) standard to a WZ video codec. The results obtained confirm the subjective quality improvement and objective quality gains that can go up to 0.63-dB in the overall for sequences with high motion content when large group of pictures are used.

Refining Side Information for Improved Transform Domain Wyner-Ziv Video Coding

Wyner-Ziv (WZ) video coding is a particular case of distributed video coding, which is a recent video coding paradigm based on the Slepian-Wolf and WZ theorems. Contrary to available prediction-based standard video codecs, WZ video coding exploits the source statistics at the decoder, allowing the development of simpler encoders. Until now, WZ video coding did not reach the compression efficiency performance of conventional video coding solutions, mainly due to the poor quality of the side information, which is an estimate of the original frame created at the decoder in the most popular WZ video codecs. In this context, this paper proposes a novel side information refinement (SIR) algorithm for a transform domain WZ video codec based on a learning approach where the side information is successively improved as the decoding proceeds. The results show significant and consistent performance improvements regarding state-of-the-art WZ and standard video codecs, especially under critical conditions such as high motion content and long group of pictures sizes.

Evaluating a feedback channel based transform domain Wyner–Ziv video codec

Wyner–Ziv (WZ) video coding—a particular case of distributed video coding (DVC)—is a new video coding paradigm based on two major Information Theory results: the Slepian–Wolf and Wyner–Ziv theorems. In recent years, some practical WZ video coding solutions have been proposed with promising results. One of the most popular WZ video coding architectures in the literature uses turbo codes based Slepian–Wolf coding and a feedback channel to perform rate control at the decoder. This WZ video coding architecture has been first proposed by researchers at Stanford University and has been after adopted and improved by many research groups around the world. However, while there are many papers published with changes and improvements to this architecture, the precise and detailed evaluation of its performance, targeting its deep understanding for future advances, has not been made. Available performance results are mostly partial, under unclear and incompatible conditions, using vaguely defined and also sometimes architecturally unrealistic codec solutions. This paper targets the provision of a detailed, clear, and complete performance evaluation of an advanced transform domain WZ video codec derived from the Stanford turbo coding and feedback channel based architecture. Although the WZ video codec proposed for this evaluation is among the best available, the main purpose and novelty of this paper is the solid and comprehensive performance evaluation made which will provide a strong, and very much needed, performance reference for researchers in this WZ video coding field, as well as a solid way to steer future WZ video coding research.