nils-herrmann/clean_scirepeval huggingface dataset:
Combined scalability support for the scalable extension of H.264/AVC

The scalability extension of H.264/AVC (H. Schwarz, et al., 2004) uses a layered approach for providing spatial, temporal, and SNR scalability. Due to this concept, only a restricted set of spatio-temporal-SNR points can be extracted and decoded from a global scalable bit-stream, and this set of points is defined by the chosen encoder configuration. In this paper, we present a new approach for providing flexible combined spatial, temporal, and SNR scalability. The increased flexibility is achieved by introducing NAL units that represent a refinement signal for a picture in a coarse-to-fine-description and can be truncated at any arbitrary point. The simulation results show that this approach is capable of providing flexible combined scalability while the coding efficiency is only slightly worse than that of the layered approach.
Video compression using context-based adaptive arithmetic coding

A new entropy coding scheme for video compression is presented. Context models are utilized for efficient prediction of the coding symbols. A novel binary adaptive arithmetic coding technique is employed to match the conditional entropy of the coding symbols given the context model estimates. The adaptation is also employed to keep track of non-stationary symbol statistics. Our new approach has been integrated into the current ITU-T H.26L test model (TML) to demonstrate the performance gain. By using our new entropy coding scheme instead of the variable length code approach of the current TML, large bit-rate savings up to 32% can be achieved. As a remarkable outcome of our experiments, we observed that high gains are reached not only at high bit-rates, but also at very low rates.
Transform codinginthe HEVC Test Model

Recently, ITU-T VCEG and ISO/IEC MPEG have started a new joint standardization activity on video coding, called High Efficiency Video Coding (HEVC). In this paper, the new transform coding techniques in the HEVC Test Model are described, including the residual quadtree (RQT) approach and coded block pattern signaling. Experimental results showing the advantage of using larger block size transforms, especially for high resolution video material, are presented. Furthermore, the trade-off between coding gain and encoder complexity in terms of the maximum RQT depth is discussed.
3D video: Depth coding based on inter-component prediction of block partitions

This paper presents a new approach for 3D video coding, where the video and the depth component of an MVD representation are jointly coded in an integrated framework. This enables a new type of prediction for exploiting the correlations of video and depth signals in addition to existing methods for temporal and inter-view prediction. Our new method is referred to as inter-component prediction and we adopt it for predicting non-rectangular partitions in depth blocks. By dividing the block into two regions, each represented with a constant value, such block partitions are well-adapted to the characteristics of depth maps. The results show that this approach reduces the bit rate of the depth component by up to 11% and leads to an increased quality of rendered views.
Connecting the worlds: Multipoint videoconferencing integrating H.323 and IPv4, SIP and IPv6 with autonomous sender authentication

In this paper we present a multipoint media conference software with extended network capabilities. Its core components combine an advanced, highly efficient H.264/AVC video coding system. Session signaling follows the SIP standard and simultaneously supports IPv4 and IPv6. Built upon an underlying peer-to-peer communication scheme, it further supports advanced integration with legacy MCUs and thereby enables hybrid sessions that extend into the H.323 world. We demonstrate how our software can span fully functional conferences across these worlds by deploying a passive gateway peer. Finally, we address security issues arising in distributed conferencing systems. It is shown, how the use of cryptographically generated identifiers enables the application to authenticate data on a packet level, thereby preventing abuse and impersonation of the conference overlay network.
Comparison of context-based adaptive binary arithmetic coders in video compression

A comparison of two context-modeling methods, CABAC and GRASP, is presented with regard to applications in video compression. Both context-based entropy coding methods are tested for various probability estimation techniques, for different sources, and for different quantization parameters by using the test model of the H.264/AVC video coding standard. Our experimental results show that GRASP provides a significant gain over CABAC, especially for intra frames coded at medium to high bit-rates.
Context-based adaptive binary arithmetic coding in the H.264/AVC video compression standard

Context-based adaptive binary arithmetic coding (CABAC) as a normative part of the new ITU-T/ISO/IEC standard H.264/AVC for video compression is presented. By combining an adaptive binary arithmetic coding technique with context modeling, a high degree of adaptation and redundancy reduction is achieved. The CABAC framework also includes a novel low-complexity method for binary arithmetic coding and probability estimation that is well suited for efficient hardware and software implementations. CABAC significantly outperforms the baseline entropy coding method of H.264/AVC for the typical area of envisaged target applications. For a set of test sequences representing typical material used in broadcast applications and for a range of acceptable video quality of about 30 to 38 dB, average bit-rate savings of 9%-14% are achieved.
Improved context modeling for coding quantized transform coefficients in video compression

Recent investigations have shown that the support of extended block sizes for motion-compensated prediction and transform coding can significantly increase the coding efficiency for high-resolution video relative to H.264/AVC. In this paper, we present a new context-modeling scheme for the coding of transform coefficient levels that is particularly suitable for transform blocks greater than 8×8. While the basic concept for transform coefficient coding is similar to CABAC, the probability model selection has been optimized for larger block transforms. The proposed context modeling is compared to a straightforward extension of the CABAC context modeling; both schemes have been implemented in a hybrid video codec design that supports block sizes of up to 128×128 samples. In our simulations, we obtained overall bit rate reductions of up to 4%, with an average of 1.7% with the proposed context modeling scheme.
A Context Modeling Scheme for Coding of Texture Refinement Information

Fidelity scalability involves the refinement of residual texture information. The entropy coding of texture refinement information in the scalable video coding (SVC) extension of H.264/AVC relies on a simple statistical model that is tuned to an encoder-specific way of quantization for generating a single fidelity enhancement layer on top of the backward compatible base layer. For fidelity enhancement layers above the first layer, we demonstrate how and why the current model fails to properly reflect the statistics of texture refinement information. By analyzing the specific properties of the typical quantization process in fidelity scalable coding of SVC, we are able to derive a generic modeling approach for coding of refinement symbols, independent of the specific choice of dead-zone parameters and classification rules. Experimental results for a broad range of quantization parameters show averaged bit-rate savings of around 5% (relative to the total bit rate) by using our proposed context modeling approach for a representative set of video sequences in a test scenario including up to three fidelity enhancement layers.
A context modeling algorithm and its application in video compression

A new algorithm for context modeling of binary sources with application to video compression is presented. Our proposed method is based on a tree rearrangement and tree selection process for an optimized modeling of binary context trees. We demonstrate its use for adaptive context-based coding of selected syntax elements in a video coder. For that purpose we apply our proposed technique to the H.264/AVC standard and evaluate its performance for different sources and different quantization parameters. Experimental results show that by using our proposed algorithm coding gains similar or superior to those obtained with the H.264/AVC CABAC algorithm is achieved.
Cross-Component Prediction in HEVC

Video coding in the YCbCr color space has been widely used, since it is efficient for compression, but it can result in color distortion due to conversion error. Meanwhile, coding in the RGB color space maintains high color fidelity, having the drawback of a substantial bitrate increase with respect to YCbCr coding. Cross-component prediction (CCP) efficiently compresses video content by decorrelating color components while keeping high color fidelity. In this scheme, the chroma residual signal is predicted from the luma residual signal inside the coding loop. This paper gives a description of the CCP scheme from several points of view, from theoretical background to practical implementation. The proposed CCP scheme has been evaluated in standardization communities and adopted into H.265/High Efficiency Video Coding (HEVC) Range Extensions. The experimental results show significant coding performance improvements for both natural and screen content video, while the quality of all color components is maintained. The average coding gains for natural video are 17% and 5% bitrate reduction in the case of intra coding and 11% and 4% in the case of inter coding for RGB and YCbCr coding, respectively, while the average increment of encoding and decoding times in the HEVC reference software implementation are 10% and 4%, respectively.
A kernel-based statistical analysis of the residual error in video coding

Video compression techniques exploit the statistical redundancy present in video signals to efficiently reduce the amount of information sent to the decoder. We contribute with a kernel-based analysis of the residual error blocks. In particular, we borrow dimension reduction techniques from machine learning, namely Principal Component Analysis (PCA) and nonlinear Kernel Principal Component Analysis (KPCA), to assess the spatial structure of block residuals. Interestingly, a nonlinear structure is observed that correlates to the rate-distortion costs of the blocks. Simulations by using a test set of videos with cropped Ultra High Definition (UHD) resolution show interesting results.
Optimized temporal scalability for H.264 based codecs and its applications to video conferencing

In this paper, we describe and analyze a low complexity scalable video codec that extends our H.264-implementation DAVC. We can show that DSVC, our temporally scaled codec, attains an RD performance identical to the non-scaled version at comparable configuration. We achieve this by QP cascading, a method of assigning gradual refining quantization parameters to the declining temporal layers. The different quantization of frames does not lead to visual distinguishable quality fluctuations. This video codec is the core component of a software-based multipoint videoconference system, which works without MCU on a hybrid P2P network structure.
Block adaptive selection of multiple core transforms for video coding

Transform coding tools in video coding have traditionally relied on the Discrete Cosine Transform Type II (DCT-II) to map residual signals to a new domain where quantization and entropy coding tools achieve a better coding efficiency than in the spatial domain. However, the DCT-II is not sufficient to model all different types of residual signals efficiently, especially in the intra-predicted blocks case. For this reason, the DST-VII was introduced in H.265/High Efficiency Video Coding (HEVC) in order to improve the compression performance of 4 × 4 intra-predicted blocks. In this paper we propose a multiple core transform approach, in which each transform is separable and generated by combining two one-dimensional transforms for the vertical and horizontal directions. The pair of 1-D transforms is selected from a set of three different types of Discrete Trigonometric Transforms and the Identity Transformation. Test results show that the proposed algorithm achieves bit rate reductions of 3% on average with respect to HEVC for intra-predicted residuals.
H.264/MPEG4-AVC fidelity range extensions: tools, profiles, performance, and application areas

The technical work on the first amendment of the H.264/MPEG4-AVC video coding standard has recently been completed. In these so-called fidelity range extensions (FRExt) a set of new coding tools is specified which is primarily targeted at providing significant improvements in coding efficiency for higher-fidelity video material. This paper presents an overview of the corresponding methods, briefly discusses some important aspects regarding profiles and applications, and finally provides experimental results for a performance comparison with existing coding technology.
Reduced-complexity entropy coding of transform coefficient levels using truncated golomb-rice codes in video compression

In hybrid video coding, the difference between the intra or inter prediction signal and the original signal is transmitted using block-based transform coding. The state-of-the-art in coding the quantized transform coefficients is the approach specified in H.264/AVC for context-adaptive binary arithmetic coding. It has, however, been shown that the number of binary symbols that have to be arithmetically coded for the transform coefficients can become very large, making the concept less attractive for high rate applications. To overcome this issue, we propose a combination of simple variable-length codes and context-adaptive binary coding, which yields the same coding efficiency as the H.264/AVC transform coefficient coding at a lower complexity level and which has been adopted into the HEVC test model (HM).
Wavelet-based very low bit-rate video coding using image warping and overlapped block motion compensation

The authors present an algorithm for very low bit-rate video coding that combines new ideas in motion estimation, wavelet filter design, and wavelet-based coding techniques. A new motion compensation technique using image warping and overlapped block motion compensation is proposed to reduce temporal redundancies in a given image sequence. This combined motion model has the advantage of representing more complex motion than simple block matching schemes. To further improve the quality of the temporal prediction, an adaptive grid with variable density according to the varying motion activity of a given scene is generated. An adaptively switched high-quality texture interpolation is employed to cope with the problem of fractional displacements in such a way that both objective and subjective reconstruction quality is improved. Spatial decorrelation of the motion compensated residual images is performed using an one-parametric family of biorthogonal infinite impulse response (IIR) wavelet filters coupled with the highly efficient pre-coding scheme of ‘partitioning, aggregation and conditional coding’ (PACC). Experimental results demonstrate significant improvements in objective quality of 1.0–2.3 dB PSNR in comparison to the H.263+ test model TMN10 using advanced coding options. In addition, the authors' intracoding method provides a performance gain of 0.5 dB PSNR on the average for a test suite of various still images when compared to the emerging still image coding standard JPEG-2000.
A Scalable Video Coding Extension of HEVC

The paper describes a scalable video coding extension of the upcoming HEVC video coding standard for spatial and quality scalable coding. Besides coding tools known from scalable profiles of prior video coding standards, it includes new coding tools that further improve the enhancement layer coding efficiency. The effectiveness of the proposed scalable HEVC extension is demonstrated by comparing the coding efficiency to simulcast and single-layer coding for several test sequences and coding conditions.
Efficient fine granular scalable video coding

We present an efficient fine granular scalable video compression scheme which supports a fast bit rate adaptation independent of the encoder. The proposed scheme generates an embedded bitstream for each frame or, by appropriate multiplexing, for each group of picture. This rate-scalability is supported by an embedded bitstream which allows decoding at multiple rates, or to be more specific at virtually any rate. Drift removing techniques based on intra refresh or feedback mechanisms are presented. We show the potential of this video codec for variable bit rate channels as well as in combination with an unequal erasure protection scheme for error robust and efficient transmission over packet erasure channels. Possible enhancements of the presented coding schemes are discussed.
Complexity-constrained best-basis wavelet packet algorithm for image compression

The concept of adapted waveform analysis using a best-basis selection out of a predefined library of wavelet packet (WP) bases allows an efficient image representation for the purpose of compression. Image coding methods based on the best-basis WP representation have shown significant coding gains for some image classes compared with methods using a fixed dyadic structured wavelet basis, at the expense however, of considerably higher computational complexity. A modification of the best-basis method, the so-called complexity constrained best-basis algorithm (CCBB), is proposed which parameterises the complexity gap between the fast (standard) wavelet transform and the best wavelet packet basis of a maximal WP library. This new approach allows a 'suboptimal' best basis to be found with respect to a given budget of computational complexity or, in other words, it offers an instrument to control the trade-off between compression speed and, coding efficiency. Experimental results are presented for image coding applications showing a highly nonlinear relationship between the rate-distortion performance and the computational complexity in such a way that a relatively small increase in complexity with respect to the standard wavelet basis results in a relatively high rate distortion gain.
Network-optimized adaptive SVC-based live video streaming

In this work, a network-optimized live scalable video streaming scheme with adaptive preprocessing is presented, while showing significant improvements in visual quality. According to the proposed scheme, an adaptive pre-filter is applied prior to encoding each Scalable Video Coding (SVC) layer, while each pre-filter parameters are dynamically adjusted according to varying network conditions, such as the network Round Trip Time (RTT) and packet loss ratio, thereby enabling to continuously obtain an optimal visual quality at the decoder side. The performance of the presented scheme is evaluated and tested in detail, thereby demonstrating a significant gain of up to 5dB.
Context-Based Fractional Sample Refinement for HEVC Compliant Encoding

The H.265/MPEG-H High Efficiency Video Coding compliant encoding process faces the challenge of high computational complexity. Particularly, in the case of inter-picture prediction, most of the computational resources are allocated for the motion estimation (ME) process. In turn, ME and motion compensation enable improving coding efficiency by addressing the blocks of video frames as corresponding displacements from one or more reference blocks. These displacements do not necessarily have to be limited to integer sample positions, but may have an accuracy of half sample or quarter sample positions, which are identified during fractional sample refinement. In this paper, a context-based scheme for fractional sample refinement is proposed. The scheme takes the advantage of already obtained information in prior ME steps and provides significant flexibility in terms of parameterization. In this way, it adaptively achieves a desired tradeoff between computational complexity and coding efficiency. According to the experimental results obtained for an example algorithm utilizing the proposed framework, a significant decrease in the number of search points can be achieved. For instance, considering only 6 instead of 16 fractional sample positions results in a tradeoff of only 0.4% Bjøntegaard Delta-rate loss for high-definition video sequences compared with the conventional interpolation-and-search method.
Wireless Broadcasting Using the Scalable Extension of H. 264/AVC

For the ongoing standardization activities for IP-based broadcast video and audio streaming services over DVB H, DMB or 3GPP’s MBMS the use of new forward error protection techniques is investigated, since these activities only propose the use of equal error protection schemes. Especially in distributing video hierarchical protection schemes can be used for more efficient content aware protection. Even older video coding standards allow simple quality reducing mechanism like temporal scalability. New scalable video coding schemes like the scalable extensions of H. 264/AVC can be used for a further enhancement of the protection schemes. In combination with an unequal erasure protection scheme the efficiency of network delivery can be enhanced significantly. We propose a scheme, which shows benefits compared to single layer stream protection schemes. The scheme allows protection over a larger range of error rates compared to single layer protection while showing “ graceful degradation” like behavior.
A wavelet-based video coding scheme using image warping prediction

This paper describes a video coding algorithm that combines new ideas in motion estimation and wavelet-based coding techniques. A motion estimation technique using an image warping model is employed to reduce temporal redundancies in a given image sequence. The underlying continuous motion model is based on a bilinear warp of a grid of quadrangles. It has the advantage of dealing with more complex motion than simple block matching schemes. In addition, a block adaptive high-quality texture interpolation is used to further improve the quality of the prediction. The prediction error image is decorrelated using a wavelet transform coupled with a framework of highly efficient pre-coding techniques utilizing the concepts of partitioning, aggregation and conditional coding (PACC). This combined coding strategy has proved to be very efficient both with respect to subjective and objective measures. The improvements achieved with our proposed coder compared to the H.263 coder (with all options applied) range from 0.5 to 1.2 dB PSNR. Especially at very low bit-rates where reconstructed videos of block-based coders suffer from visually annoying blocking artifacts the proposed coding scheme produces a superior subjective quality.