3D video compression based on high efficiency video coding

With the advent of autostereoscopic displays, questions rise on how to efficiently compress the video information needed by such displays. Additionally, for gradual market acceptance of this new technology it is valuable to have a solution offering forward compatibility with stereo 3D video as it is used nowadays. In this paper, a multiview compression scheme making use of the efficient single-view coding tools used in High Efficiency Video Coding (HEVC) is provided. Although efficient single view compression can be obtained with HEVC, a multiview adaptation of this standard under development is proposed, offering additional coding gains. On average, for the texture information, the total bitrate can be reduced by 37.2% compared to simulcast HEVC. For depth map compression, gains largely depend on the quality of the captured content. Additionally, a forward compatible solution is proposed offering the possibility for a gradual upgrade from H.264/AVC based stereoscopic 3D systems to an HEVC-based autostereoscopic environment. With the proposed system, significant rate savings compared to Multiview Video Coding (MVC) are presented(1)

Subjective Evaluation of Next-Generation Video Compression Algorithms: A Case Study

This paper describes the details and the results of the subjective quality evaluation performed at EPFL, as a contribution to the effort of the Joint Collaborative Team on Video Coding (JCT-VC) for the definition of the next-generation video coding standard. The performance of 27 coding technologies have been evaluated with respect to two H.264/MPEG-4 AVC anchors, considering high definition (HD) test material. The test campaign involved a total of 494 naive observers and took place over a period of four weeks. While similar tests have been conducted as part of the standardization process of previous video coding technologies, the test campaign described in this paper is by far the most extensive in the history of video coding standardization. The obtained subjective quality scores show high consistency and support an accurate comparison of the performance of the different coding solutions

Quality Evaluations and algorithmic Improvement of the next Generation Video Coding - HEVC

The increased processing power and screen sizes of mobile devices has made it desirable to watch multimedia presentations on the go. On such devices the data network bandwidth is usually the limiting factor, which imposes a tradeoff between quality and resolution on the presented content. A new video compression system called High Efficiency Video Coding (HEVC) is currently under development. The vision of HEVC is to create a compression system that achieves the same quality at half the bit rate compared to the existing H.264/AVC standard [2].The goal of this thesis is to investigate how HEVC performs compared to H.264/AVC using mobile platforms and sport content as the scenario. The subjective test was conducted on an Apple iPad. It indicated that HEVC has a clear gain in compression compared to H.264/AVC. On average at a resolution of 640x368, HEVC achieved a good quality rating at approximately 550 kilobit per second while H.264/AVC did almost reach this quality at 1000 kilobit per second. However, it was shown that subjective quality gain varied over content.The objective measurements showed an overall reduction in bit rate of 32% forthe luma component. However, the reduction of bit rate was highly variable over content and resolution. A high correlation between the subjective and objective measurements was found, which indicates that it was almost a linear relationship between the reported subjective and objective results.In addition, a proposed deblocking filter was implemented. The filter applies a new filter function of the luma samples and performs line based filtering decision. On average the reduction in bit rate was reported to be 0.4%, with a maximum reduction of 0.8% for the luma component. The decoding time relative to the second version of the HEVC test model was reported to be 1.5% higher. This is most likely due to the line based filtering decision. The general impression of HEVC is that it has the ability to reach the stated vision, and perhaps even surpass, when finalized

Piecewise mapping in HEVC lossless intra-prediction coding

The lossless intra-prediction coding modality of the High Efficiency Video Coding (HEVC) standard provides high coding performance while following frame-by-frame basis access to the coded data. This is of interest in many professional applications such as medical imaging, automotive vision and digital preservation in libraries and archives. Various improvements to lossless intra-prediction coding have been proposed recently, most of them based on sample-wise prediction using Differential Pulse Code Modulation (DPCM). Other recent proposals aim at further reducing the energy of intra-predicted residual blocks. However, the energy reduction achieved is frequently minimal due to the difficulty of correctly predicting the sign and magnitude of residual values. In this paper, we pursue a novel approach to this energy-reduction problem using piecewise mapping (pwm) functions. Specifically, we analyze the range of values in residual blocks and apply accordingly a pwm function to map specific residual values to unique lower values. We encode appropriate parameters associated with the pwm functions at the encoder, so that the corresponding inverse pwm functions at the decoder can map values back to the same residual values. These residual values are then used to reconstruct the original signal. This mapping is, therefore, reversible and introduces no losses. We evaluate the pwm functions on 4×4 residual blocks computed after DPCM-based prediction for lossless coding of a variety of camera-captured and screen content sequences. Evaluation results show that the pwm functions can attain maximum bit-rate reductions of 5.54% and 28.33% for screen content material compared to DPCM-based and block-wise intra-prediction, respectively. Compared to IntraBlock Copy, piecewise mapping can attain maximum bit-rate reductions of 11.48% for camera-captured material

COOL-CHIC: Coordinate-based Low Complexity Hierarchical Image Codec

We introduce COOL-CHIC, a Coordinate-based Low Complexity Hierarchical Image Codec. It is a learned alternative to autoencoders with approximately 2000 parameters and 2500 multiplications per decoded pixel. Despite its low complexity, COOL-CHIC offers compression performance close to modern conventional MPEG codecs such as HEVC and VVC. This method is inspired by the Coordinate-based Neural Representation, where an image is represented as a learned function which maps pixel coordinates to RGB values. The parameters of the mapping function are then sent using entropy coding. At the receiver side, the compressed image is obtained by evaluating the mapping function for all pixel coordinates. COOL-CHIC implementation is made available upon request

Algorithms and methods for video transcoding.

Video transcoding is the process of dynamic video adaptation. Dynamic video adaptation can be defined as the process of converting video from one format to another, changing the bit rate, frame rate or resolution of the encoded video, which is mainly necessitated by the end user requirements. H.264 has been the predominantly used video compression standard for the last 15 years. HEVC (High Efficiency Video Coding) is the latest video compression standard finalised in 2013, which is an improvement over H.264 video compression standard. HEVC performs significantly better than H.264 in terms of the Rate-Distortion performance. As H.264 has been widely used in the last decade, a large amount of video content exists in H.264 format. There is a need to convert H.264 video content to HEVC format to achieve better Rate-Distortion performance and to support legacy video formats on newer devices. However, the computational complexity of HEVC encoder is 2-10 times higher than that of H.264 encoder. This makes it necessary to develop low complexity video transcoding algorithms to transcode from H.264 to HEVC format. This research work proposes low complexity algorithms for H.264 to HEVC video transcoding. The proposed algorithms reduce the computational complexity of H.264 to HEVC video transcoding significantly, with negligible loss in Rate-Distortion performance. This work proposes three different video transcoding algorithms. The MV-based mode merge algorithm uses the block mode and MV variances to estimate the split/non-split decision as part of the HEVC block prediction process. The conditional probability-based mode mapping algorithm models HEVC blocks of sizes 16×16 and lower as a function of H.264 block modes, H.264 and HEVC Quantisation Parameters (QP). The motion-compensated MB residual-based mode mapping algorithm makes the split/non-split decision based on content-adaptive classification models. With a combination of the proposed set of algorithms, the computational complexity of the HEVC encoder is reduced by around 60%, with negligible loss in Rate-Distortion performance, outperforming existing state-of-art algorithms by 20-25% in terms of computational complexity. The proposed algorithms can be used in computation-constrained video transcoding applications, to support video format conversion in smart devices, migration of large-scale H.264 video content from host servers to HEVC, cloud computing-based transcoding applications, and also to support high quality videos over bandwidth-constrained networks