1,115 research outputs found
A parallel H.264/SVC encoder for high definition video conferencing
In this paper we present a video encoder specially developed and configured for high definition (HD) video conferencing. This video encoder brings together the following three requirements: H.264/Scalable Video Coding (SVC), parallel encoding on multicore platforms, and parallel-friendly rate control. With the first requirement, a minimum quality of service to every end-user receiver over Internet Protocol networks is guaranteed. With the second one, real-time execution is accomplished and, for this purpose, slice-level parallelism, for the main encoding loop, and block-level parallelism, for the upsampling and interpolation filtering processes, are combined. With the third one, a proper HD video content delivery under certain bit rate and end-to-end delay constraints is ensured. The experimental results prove that the proposed H.264/SVC video encoder is able to operate in real time over a wide range of target bit rates at the expense of reasonable losses in rate-distortion efficiency due to the frame partitioning into slices
Low-Complexity Joint Temporal-Quality Scalability Rate Control for H.264/SVC
Rate control in scalable video coding (SVC) is a very challenging problem because of the inter-layer prediction structure, which makes developing an efficient rate-control algorithm complex and difficult. Little prior work is available for joint temporal-quality (T-Q) scalability considering the rate-distortion (R-D) dependence among the temporal and quality layers. However, most of the rate-control algorithms in SVC suffer from high computational complexity, growing significantly with the number of layers. In this paper, a single-pass joint temporal-quality rate-control algorithm is presented for H.264/SVC. In this algorithm, by analyzing the R-D dependence of joint T-Q scalability, Cauchy distribution-based rate-quantization, and distortion-quantization models, a set of empirical values are first derived to estimate the initial values of the R-D model parameters for the joint temporal and quality layers. Then, a novel prediction mechanism to update these model parameters is proposed to allocate the bit budgets efficiently among the temporal and quality layers, and hence to improve the performance of the proposed algorithm. Experimental results show that the proposed algorithm achieves better coding efficiency with low computational complexity compared with two other benchmark rate-control algorithms
Rate Control Initialization Algorithm for Scalable Video Coding
Proceeding of: 18th IEEE International Conference on Image Processing (ICIP), 2011.In this paper we propose a novel rate control initialization algorithm for real-time H.264/scalable video coding. In particular, a two-step approach is proposed. First, the initial quantization parameter (QP) for each layer is determined by means of a parametric rate-quantization (R-Q) modeling that depends on the layer identifier (base or enhancement) and on the type of scalability (spatial or quality). Second, an intra-frame QP refinement method that allows for adapting the initial QP value when needed is carried out over the three first coded frames in order to take into consideration both the buffer control and the spatio-temporal complexity of the scene. The experimental results show that the proposed R-Q modeling for initial QP estimation, in combination with the intra-frame QP refinement method, provide a good performance in terms of visual quality and buffer control, achieving remarkably similar results to those achieved by using ideal initial QP values.The Spanish National grant TSI-020110-2009-103 (AFICUS) and the Regional grant CCG10-UC3M/TIC-5570 (AMASSACA).Publicad
Enabling Quality-Driven Scalable Video Transmission over Multi-User NOMA System
Recently, non-orthogonal multiple access (NOMA) has been proposed to achieve
higher spectral efficiency over conventional orthogonal multiple access.
Although it has the potential to meet increasing demands of video services, it
is still challenging to provide high performance video streaming. In this
research, we investigate, for the first time, a multi-user NOMA system design
for video transmission. Various NOMA systems have been proposed for data
transmission in terms of throughput or reliability. However, the perceived
quality, or the quality-of-experience of users, is more critical for video
transmission. Based on this observation, we design a quality-driven scalable
video transmission framework with cross-layer support for multi-user NOMA. To
enable low complexity multi-user NOMA operations, a novel user grouping
strategy is proposed. The key features in the proposed framework include the
integration of the quality model for encoded video with the physical layer
model for NOMA transmission, and the formulation of multi-user NOMA-based video
transmission as a quality-driven power allocation problem. As the problem is
non-concave, a global optimal algorithm based on the hidden monotonic property
and a suboptimal algorithm with polynomial time complexity are developed.
Simulation results show that the proposed multi-user NOMA system outperforms
existing schemes in various video delivery scenarios.Comment: 9 pages, 6 figures. This paper has already been accepted by IEEE
INFOCOM 201
Complexity Analysis Of Next-Generation VVC Encoding and Decoding
While the next generation video compression standard, Versatile Video Coding
(VVC), provides a superior compression efficiency, its computational complexity
dramatically increases. This paper thoroughly analyzes this complexity for both
encoder and decoder of VVC Test Model 6, by quantifying the complexity
break-down for each coding tool and measuring the complexity and memory
requirements for VVC encoding/decoding. These extensive analyses are performed
for six video sequences of 720p, 1080p, and 2160p, under Low-Delay (LD),
Random-Access (RA), and All-Intra (AI) conditions (a total of 320
encoding/decoding). Results indicate that the VVC encoder and decoder are 5x
and 1.5x more complex compared to HEVC in LD, and 31x and 1.8x in AI,
respectively. Detailed analysis of coding tools reveals that in LD on average,
motion estimation tools with 53%, transformation and quantization with 22%, and
entropy coding with 7% dominate the encoding complexity. In decoding, loop
filters with 30%, motion compensation with 20%, and entropy decoding with 16%,
are the most complex modules. Moreover, the required memory bandwidth for VVC
encoding/decoding are measured through memory profiling, which are 30x and 3x
of HEVC. The reported results and insights are a guide for future research and
implementations of energy-efficient VVC encoder/decoder.Comment: IEEE ICIP 202
A Simple and High Performing Rate Control Initialization Method for H.264 AVC Coding Based on Motion Vector Map and Spatial Complexity at Low Bitrate
The temporal complexity of video sequences can be characterized by motion vector map which consists of motion vectors of each macroblock (MB). In order to obtain the optimal initial QP (quantization parameter) for the various video sequences which have different spatial and temporal complexities, this paper proposes a simple and high performance initial QP determining method based on motion vector map and temporal complexity to decide an initial QP in given target bit rate. The proposed algorithm produces the reconstructed video sequences with outstanding and stable quality. For any video sequences, the initial QP can be easily determined from matrices by target bit rate and mapped spatial complexity using proposed mapping method. Experimental results show that the proposed algorithm can show more outstanding objective and subjective performance than other conventional determining methods
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