Sebastiaan Van Leuven

Motion-based temporal transcoding from H.264/AVC-to-SVC in baseline profile

Video contents needs to be compressed in order to reduce the resources required for storage and network transmission. It is desirable that the encoded bitstreams are adaptable to the varying characteristics of consumer electronics devices and heterogeneous networks. Scalable Video Coding provides temporal, spatial and quality scalability by organizing the encoded bitstream into layers. Since the majority of the produced video content is currently encoded using H.264/AVC, it will be necessary to implement techniques for converting from single-layer H.264/AVC to scalable bitstreams. In this paper, a technique for transcoding from H.264/AVC-to-SVC with temporal scalability in Baseline Profile is discussed. Applying the presented approach, a reduction of 64% of the coding complexity is achieved while maintaining the coding efficiency.

Improved intra mode signaling for HEVC

In the current development of HEVC, compression performance improved significantly compared to H.264/AVC for both inter pictures and intra pictures. With intra compression, the main reason for this improvement is the large increase in intra prediction directions (up to 34). The downside of having a larger number of modes is that they increase the signaling overhead in the bitstream. In this paper, a low complexity intra mode prediction algorithm is proposed which improves the mode prediction accuracy. This is achieved by exploiting the correlation between the prediction directions of the neighboring prediction units and that of the encoded prediction unit. As a result, more efficient intra mode signaling can be achieved with minimal impact on encoder and decoder complexity. On average, 0.33% bitrate improvement is obtained by employing the proposed algorithm. For sequences that are encoded with a high number of directional intra modes, around 1% bitrate improvement is measured.

Fast transrating for high efficiency video coding based on machine learning

To incorporate the newly developed High Efficiency Video Coding (HEVC) standard in real-life network applications, efficient transrating algorithms are required. We propose a fast transrating scheme, based on the early prediction of the partition split-flags in P pictures. Using machine learning techniques, the correlation between co-located partitions at different quantizations is investigated. This results in a model which predicts the split-flag and gives the associated prediction accuracy so that the splitting process in the transcoder is optimized. At each partition depth, the model indicates whether the full rate-distortion cost evaluations should be performed at the current depth, or if the partition can be split immediately. Experimental results show that the proposed transcoder reduces the complexity of the transrating process by 76.04%, while maintaining the coding efficiency of a cascaded decoder-encoder.

Fast H.264/AVC-to-SVC Transcoding in a Mobile Television Environment

Mobile TV environments demand flexible video compression like Scalable Video Coding (SVC) because of varying bandwidths and devices. Since existing infrastructures highly rely on H.264/AVC video compression, network providers could adapt the current H.264/AVC encoded video to SVC. This adaptation needs to be done efficiently to reduce processing power and operational cost. Since a cascaded decoder-encoder solution is too complex to be practical, we developed a mechanism to encode scalable video streams from existing H.264/AVC encoded video streams. This paper proposes a novel technique to accelerate the encoding of SVC streams by reusing information from the H.264/AVC stream and the base layer. We achieved a complexity reduction of 52%, while only an insignificant bit rate increase is reported (0.2%). According to these results, an H.264/AVC-to-SVC transcoder is usable with a low operational cost without compromising the coding efficiency.

Efficient Bit Rate Transcoding for High Efficiency Video Coding

High efficiency video coding (HEVC) shows a significant advance in compression efficiency and is considered to be the successor of H.264/AVC. To incorporate the HEVC standard into real-life network applications and a diversity of other applications, efficient bit rate adaptation (transrating) algorithms are required. A current problem of transrating for HEVC is the high computational complexity associated with the encoder part of such a cascaded pixel domain transcoder. This paper focuses on deriving an optimal strategy for reducing the transcoding complexity with a complexity-scalable scheme. We propose different transcoding techniques which are able to reduce the transcoding complexity in both CU and PU optimization levels. At the CU level, CUs can be evaluated in top-to-bottom or bottom-to-top flows, in which the coding information of the input video stream is utilized to reduce the number of evaluations or to early terminate certain evaluations. At the PU level, the PU candidates are adaptively selected based on the probability of PU sizes and the co-located input PU partitioning. Moreover, with the use of different proposed methods, a complexity-scalable transrating scheme can be achieved. Furthermore, the transcoding complexity can be effectively controlled by the machine learning based approach. Simulations show that the proposed techniques provide a superior transcoding performance compared to the state-of-the-art related works. Additionally, the proposed methods can achieve a range of trade-offs between transrating complexity and coding performance. From the proposed schemes, the fastest approach is able to reduce the complexity by 82% while keeping the bitrate loss below 3%.

Fast motion estimation for closed-loop HEVC transrating

Transrating is a useful tool for adapting the bitrate of a video stream. Reducing the complexity of transrating is extremely important, especially for high efficiency video coding (HEVC) based transrating where the encoder is very time consuming. TZSearch is currently the default integer motion estimation (ME) algorithm in the HEVC reference encoder thanks to its excellent performance in reducing the complexity of ME. However, this algorithm is characterized by a fixed search area and search pattern, which can be considered sub optimal for transrating. In this paper, we improve the performance of HEVC transrating by optimizing this TZSearch algorithm. Utilizing the correlation between input and output motion vectors, we propose a fast search scheme including three steps. First, the initial search point is selected. Then, using the rate-distortion cost of this starting point, the search size is determined according to an online-trained Bayes decision rule. Finally, two proposed search algorithms are described for refining the starting point. Experimental results show that our proposed TZSearch scheme can reduce the complexity of transrating while improving the coding performance in terms of bit rate saving.

Format-compliant encryption techniques for high efficiency video coding

When middlebox devices should be able to adapt an encrypted video stream in the network without having the decryption key, format-compliant partial encryption schemes should be applied. In this paper, we propose such encryption schemes for the recently standardized High Efficiency Video Coding (HEVC) standard. By encrypting specific syntax elements like the sign of the residual information, the sign of the motion vector (MV) difference, the MV prediction index, and the MV reference index, format compliance and the possibility for adaptation are offered. Scrambling performance gradually increases when shifting from encrypting the motion information to encrypting the residual sign and finally to the combination thereof. Applying all these techniques has a negligible impact on the compression efficiency.

Video transcoding for mobile digital television

Mobile digital television is one of the new services introduced recently by telecommunications operators. Due to the possibilities of personalization and interaction provided, together with the increasing demand for this type of portable services, it will undoubtedly be a successful technology in the near future. Multimedia content is generally encoded by reducing the storage capacity necessary and bandwidth consumption in order to be transmitted. In order to adapt to the different characteristics of the networks and the varying capabilities of the devices, scalable video coding schemes have been proposed that provide temporal, spatial, and quality scalability, or a combination of these. Most of the existing video content is compressed using H.264/AVC, which is a single-layer codec, so these contents cannot benefit from the scalability tools due to the lack of intrinsic scalability provided in the bitstream at encoding time. This paper proposes a technique to convert from the single-layer H.264/AVC bitstream to a scalable bitstream with temporal scalability. Applying this approach, a reduction of 60% in coding complexity is achieved while maintaining the coding efficiency.

Combining open — And closed-loop architectures for H.264/AVC-TO-SVC transcoding

Scalable video coding (SVC) allows encoded bitstreams to be adapted. However, most bitstreams do not incorporate this scalability so bitstreams have to be adapted multiple times to accommodate for varying network conditions or end-user devices. Each adaptation incorporates an additional loss of quality due to transcoding. To overcome this issue, we propose a single transcoding step from H.264/AVC to SVC. Doing so, the resulting bitstream can be freely adapted without any additional quality reduction. Open-loop transcoding architectures can be used for H.264/AVC-to-SVC transcoding with a low complexity, although these architectures suffer from drift artifacts. Closed-loop transcoding, on the other hand, requires a higher complexity. To overcome the drawbacks of both systems, we propose combining both techniques.

Generic techniques to reduce SVC enhancement layer encoding complexity

Scalable video coding is an important mechanism to provide several types of end-user devices with different versions of the same encoded bitstream. However, scalable video encoding remains a computationally expensive operation. To decrease the complexity we propose generic techniques. These techniques are generic in a sense that they can be combined with existing fast mode decision methods and optimizations. We show that extending such an existing fast mode decision technique yields an average complexity reduction of 87.27%, while only an additional 0.74% of bit rate increase and a decrease of 0.11dB in PSNR is required, compared to the original fast mode decision method.