52 research outputs found
Fast Depth and Inter Mode Prediction for Quality Scalable High Efficiency Video Coding
International audienceThe scalable high efficiency video coding (SHVC) is an extension of high efficiency video coding (HEVC), which introduces multiple layers and inter-layer prediction, thus significantly increases the coding complexity on top of the already complicated HEVC encoder. In inter prediction for quality SHVC, in order to determine the best possible mode at each depth level, a coding tree unit can be recursively split into four depth levels, including merge mode, inter2Nx2N, inter2NxN, interNx2N, interNxN, in-ter2NxnU, inter2NxnD, internLx2N and internRx2N, intra modes and inter-layer reference (ILR) mode. This can obtain the highest coding efficiency, but also result in very high coding complexity. Therefore, it is crucial to improve coding speed while maintaining coding efficiency. In this research, we have proposed a new depth level and inter mode prediction algorithm for quality SHVC. First, the depth level candidates are predicted based on inter-layer correlation, spatial correlation and its correlation degree. Second, for a given depth candidate, we divide mode prediction into square and non-square mode predictions respectively. Third, in the square mode prediction, ILR and merge modes are predicted according to depth correlation, and early terminated whether residual distribution follows a Gaussian distribution. Moreover, ILR mode, merge mode and inter2Nx2N are early terminated based on significant differences in Rate Distortion (RD) costs. Fourth, if the early termination condition cannot be satisfied, non-square modes are further predicted based on significant differences in expected values of residual coefficients. Finally, inter-layer and spatial correlations are combined with residual distribution to examine whether to early terminate depth selection. Experimental results have demonstrated that, on average, the proposed algorithm can achieve a time saving of 71.14%, with a bit rate increase of 1.27%
Fast Motion Estimation Algorithms for Block-Based Video Coding Encoders
The objective of my research is reducing the complexity of video coding standards in real-time scalable and multi-view applications
Surveillance centric coding
PhDThe research work presented in this thesis focuses on the development of techniques
specific to surveillance videos for efficient video compression with higher processing
speed. The Scalable Video Coding (SVC) techniques are explored to achieve higher
compression efficiency. The framework of SVC is modified to support Surveillance
Centric Coding (SCC). Motion estimation techniques specific to surveillance videos
are proposed in order to speed up the compression process of the SCC.
The main contributions of the research work presented in this thesis are divided into
two groups (i) Efficient Compression and (ii) Efficient Motion Estimation. The
paradigm of Surveillance Centric Coding (SCC) is introduced, in which coding aims
to achieve bit-rate optimisation and adaptation of surveillance videos for storing and
transmission purposes. In the proposed approach the SCC encoder communicates
with the Video Content Analysis (VCA) module that detects events of interest in
video captured by the CCTV. Bit-rate optimisation and adaptation are achieved by
exploiting the scalability properties of the employed codec. Time segments
containing events relevant to surveillance application are encoded using high spatiotemporal
resolution and quality while the irrelevant portions from the surveillance
standpoint are encoded at low spatio-temporal resolution and / or quality. Thanks to
the scalability of the resulting compressed bit-stream, additional bit-rate adaptation is
possible; for instance for the transmission purposes. Experimental evaluation showed
that significant reduction in bit-rate can be achieved by the proposed approach
without loss of information relevant to surveillance applications.
In addition to more optimal compression strategy, novel approaches to performing
efficient motion estimation specific to surveillance videos are proposed and
implemented with experimental results. A real-time background subtractor is used to
detect the presence of any motion activity in the sequence. Different approaches for
selective motion estimation, GOP based, Frame based and Block based, are
implemented. In the former, motion estimation is performed for the whole group of
pictures (GOP) only when a moving object is detected for any frame of the GOP.
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While for the Frame based approach; each frame is tested for the motion activity and
consequently for selective motion estimation. The selective motion estimation
approach is further explored at a lower level as Block based selective motion
estimation. Experimental evaluation showed that significant reduction in
computational complexity can be achieved by applying the proposed strategy. In
addition to selective motion estimation, a tracker based motion estimation and fast
full search using multiple reference frames has been proposed for the surveillance
videos.
Extensive testing on different surveillance videos shows benefits of
application of proposed approaches to achieve the goals of the SCC
Efficient algorithms for scalable video coding
A scalable video bitstream specifically designed for the needs of various client terminals,
network conditions, and user demands is much desired in current and future video transmission
and storage systems. The scalable extension of the H.264/AVC standard (SVC) has
been developed to satisfy the new challenges posed by heterogeneous environments, as
it permits a single video stream to be decoded fully or partially with variable quality, resolution,
and frame rate in order to adapt to a specific application. This thesis presents
novel improved algorithms for SVC, including: 1) a fast inter-frame and inter-layer coding
mode selection algorithm based on motion activity; 2) a hierarchical fast mode selection
algorithm; 3) a two-part Rate Distortion (RD) model targeting the properties of different
prediction modes for the SVC rate control scheme; and 4) an optimised Mean Absolute
Difference (MAD) prediction model.
The proposed fast inter-frame and inter-layer mode selection algorithm is based on the
empirical observation that a macroblock (MB) with slow movement is more likely to be
best matched by one in the same resolution layer. However, for a macroblock with fast
movement, motion estimation between layers is required. Simulation results show that
the algorithm can reduce the encoding time by up to 40%, with negligible degradation in
RD performance.
The proposed hierarchical fast mode selection scheme comprises four levels and makes
full use of inter-layer, temporal and spatial correlation aswell as the texture information of
each macroblock. Overall, the new technique demonstrates the same coding performance
in terms of picture quality and compression ratio as that of the SVC standard, yet produces
a saving in encoding time of up to 84%. Compared with state-of-the-art SVC fast mode
selection algorithms, the proposed algorithm achieves a superior computational time reduction
under very similar RD performance conditions.
The existing SVC rate distortion model cannot accurately represent the RD properties of
the prediction modes, because it is influenced by the use of inter-layer prediction. A separate
RD model for inter-layer prediction coding in the enhancement layer(s) is therefore
introduced. Overall, the proposed algorithms improve the average PSNR by up to 0.34dB
or produce an average saving in bit rate of up to 7.78%. Furthermore, the control accuracy
is maintained to within 0.07% on average.
As aMADprediction error always exists and cannot be avoided, an optimisedMADprediction
model for the spatial enhancement layers is proposed that considers the MAD from
previous temporal frames and previous spatial frames together, to achieve a more accurateMADprediction.
Simulation results indicate that the proposedMADprediction model
reduces the MAD prediction error by up to 79% compared with the JVT-W043 implementation
Fast motion estimation algorithms for block-based video coding encoders
The objective of my research is reducing the complexity of video coding standards in real-time scalable and multi-view applications.EThOS - Electronic Theses Online ServiceGBUnited Kingdo
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