31 research outputs found
Low-Complexity TTCM Based Distributed Video Coding Architecture
Abstract. Distributed Video Coding (DVC) is a promising coding solution for some emerging applications, where the encoder complexity, power consumption or memory requirements are constraint the system resources. Current approaches to DVC focus on improving the performance of the WynerZiv coding by improving the quality of the reconstructed side information or by improving the quality of channel codes. Up to date, no attention has been paid to the problem of key frames coding where a low-encoding complexity scenario is also needed. This work focuses on key frames coding in its effect to the Wyner-Ziv frames decoding aiming to implement a very low-complexity Turbo Trellis Coded Modulation (TTCM) based DVC architecture. In this paper, we propose a new key frame coding scheme which has very low complexity and memory requirements for the TTCM based distributed video codec. Results show that the proposed intra frame codec for key frame coding outperforms the JPEG2000 and the Intra H.264 AVC codecs in terms of encoding-time and memory requirements, with better RD performance
Towards practical distributed video coding
Multimedia is increasingly becoming a utility rather than mere entertainment. The range of video applications has increased, some of which are becoming indispensable in modem lifestyle. Video surveillance is one area that has attracted significant amount of focus and also benefited from considerable research effort for development. However, it is noted that there is still a notable technological gap between an ideal video surveillance platform and the available solutions, mainly in the form of the encoder and decoder complexity balance and the associated design costs. In this thesis, we tocus on an emerging technology, Distributed Video Coding (DVC), which is ideally suited for the video surveillance scenario, and fits many other potential applications too.EThOS - Electronic Theses Online ServiceGBUnited Kingdo
Multiterminal source coding: sum-rate loss, code designs, and applications to video sensor networks
Driven by a host of emerging applications (e.g., sensor networks and wireless video),
distributed source coding (i.e., Slepian-Wolf coding, Wyner-Ziv coding and various other
forms of multiterminal source coding), has recently become a very active research area.
This dissertation focuses on multiterminal (MT) source coding problem, and consists
of three parts. The first part studies the sum-rate loss of an important special case
of quadratic Gaussian multi-terminal source coding, where all sources are positively symmetric
and all target distortions are equal. We first give the minimum sum-rate for joint
encoding of Gaussian sources in the symmetric case, and then show that the supremum of
the sum-rate loss due to distributed encoding in this case is 1
2 log2
5
4 = 0:161 b/s when L = 2
and increases in the order of
º
L
2 log2 e b/s as the number of terminals L goes to infinity.
The supremum sum-rate loss of 0:161 b/s in the symmetric case equals to that in general
quadratic Gaussian two-terminal source coding without the symmetric assumption. It is
conjectured that this equality holds for any number of terminals.
In the second part, we present two practical MT coding schemes under the framework
of Slepian-Wolf coded quantization (SWCQ) for both direct and indirect MT problems.
The first, asymmetric SWCQ scheme relies on quantization and Wyner-Ziv coding, and it
is implemented via source splitting to achieve any point on the sum-rate bound. In the second,
conceptually simpler scheme, symmetric SWCQ, the two quantized sources are compressed
using symmetric Slepian-Wolf coding via a channel code partitioning technique that is capable of achieving any point on the Slepian-Wolf sum-rate bound. Our practical
designs employ trellis-coded quantization and turbo/LDPC codes for both asymmetric and
symmetric Slepian-Wolf coding. Simulation results show a gap of only 0.139-0.194 bit per
sample away from the sum-rate bound for both direct and indirect MT coding problems.
The third part applies the above two MT coding schemes to two practical sources, i.e.,
stereo video sequences to save the sum rate over independent coding of both sequences.
Experiments with both schemes on stereo video sequences using H.264, LDPC codes for
Slepian-Wolf coding of the motion vectors, and scalar quantization in conjunction with
LDPC codes for Wyner-Ziv coding of the residual coefficients give slightly smaller sum
rate than separate H.264 coding of both sequences at the same video quality
On distributed coding, quantization of channel measurements and faster-than-Nyquist signaling
This dissertation considers three different aspects of modern digital communication
systems and is therefore divided in three parts.
The first part is distributed coding. This part deals with source and source-
channel code design issues for digital communication systems with many transmitters
and one receiver or with one transmitter and one receiver but with side information at
the receiver, which is not available at the transmitter. Such problems are attracting
attention lately, as they constitute a way of extending the classical point-to-point
communication theory to networks. In this first part of this dissertation, novel source
and source-channel codes are designed by converting each of the considered distributed
coding problems into an equivalent classical channel coding or classical source-channel
coding problem. The proposed schemes come very close to the theoretical limits and
thus, are able to exhibit some of the gains predicted by network information theory.
In the other two parts of this dissertation classical point-to-point digital com-
munication systems are considered. The second part is quantization of coded chan-
nel measurements at the receiver. Quantization is a way to limit the accuracy of
continuous-valued measurements so that they can be processed in the digital domain.
Depending on the desired type of processing of the quantized data, different quantizer
design criteria should be used. In this second part of this dissertation, the quantized
received values from the channel are processed by the receiver, which tries to recover
the transmitted information. An exhaustive comparison of several quantization cri-
teria for this case are studied providing illuminating insight for this quantizer design
problem.
The third part of this dissertation is faster-than-Nyquist signaling. The Nyquist
rate in classical point-to-point bandwidth-limited digital communication systems is
considered as the maximum transmission rate or signaling rate and is equal to twice
the bandwidth of the channel. In this last part of the dissertation, we question this
Nyquist rate limitation by transmitting at higher signaling rates through the same
bandwidth. By mitigating the incurred interference due to the faster-than-Nyquist
rates, gains over Nyquist rate systems are obtained
REGION-BASED ADAPTIVE DISTRIBUTED VIDEO CODING CODEC
The recently developed Distributed Video Coding (DVC) is typically suitable for the
applications where the conventional video coding is not feasible because of its
inherent high-complexity encoding. Examples include video surveillance usmg
wireless/wired video sensor network and applications using mobile cameras etc. With
DVC, the complexity is shifted from the encoder to the decoder.
The practical application of DVC is referred to as Wyner-Ziv video coding (WZ)
where an estimate of the original frame called "side information" is generated using
motion compensation at the decoder. The compression is achieved by sending only
that extra information that is needed to correct this estimation. An error-correcting
code is used with the assumption that the estimate is a noisy version of the original
frame and the rate needed is certain amount of the parity bits. The side information is
assumed to have become available at the decoder through a virtual channel. Due to
the limitation of compensation method, the predicted frame, or the side information, is
expected to have varying degrees of success. These limitations stem from locationspecific
non-stationary estimation noise. In order to avoid these, the conventional
video coders, like MPEG, make use of frame partitioning to allocate optimum coder
for each partition and hence achieve better rate-distortion performance. The same,
however, has not been used in DVC as it increases the encoder complexity.
This work proposes partitioning the considered frame into many coding units
(region) where each unit is encoded differently. This partitioning is, however, done at
the decoder while generating the side-information and the region map is sent over to
encoder at very little rate penalty. The partitioning allows allocation of appropriate
DVC coding parameters (virtual channel, rate, and quantizer) to each region. The
resulting regions map is compressed by employing quadtree algorithm and
communicated to the encoder via the feedback channel. The rate control in DVC is
performed by channel coding techniques (turbo codes, LDPC, etc.). The performance
of the channel code depends heavily on the accuracy of virtual channel model that models estimation error for each region. In this work, a turbo code has been used and
an adaptive WZ DVC is designed both in transform domain and in pixel domain. The
transform domain WZ video coding (TDWZ) has distinct superior performance as
compared to the normal Pixel Domain Wyner-Ziv (PDWZ), since it exploits the
'
spatial redundancy during the encoding. The performance evaluations show that the
proposed system is superior to the existing distributed video coding solutions.
Although the, proposed system requires extra bits representing the "regions map" to be
transmitted, fuut still the rate gain is noticeable and it outperforms the state-of-the-art
frame based DVC by 0.6-1.9 dB.
The feedback channel (FC) has the role to adapt the bit rate to the changing
'
statistics between the side infonmation and the frame to be encoded. In the
unidirectional scenario, the encoder must perform the rate control. To correctly
estimate the rate, the encoder must calculate typical side information. However, the
rate cannot be exactly calculated at the encoder, instead it can only be estimated. This
work also prbposes a feedback-free region-based adaptive DVC solution in pixel
domain based on machine learning approach to estimate the side information.
Although the performance evaluations show rate-penalty but it is acceptable
considering the simplicity of the proposed algorithm.
vii
Advanced distributed video coding techniques
EThOS - Electronic Theses Online ServiceGBUnited Kingdo
Distributed signal processing using nested lattice codes
Multi-Terminal Source Coding (MTSC) addresses the problem of compressing correlated sources
without communication links among them. In this thesis, the constructive approach of this problem
is considered in an algebraic framework and a system design is provided that can be applicable
in a variety of settings. Wyner-Ziv problem is first investigated: coding of an independent and
identically distributed (i.i.d.) Gaussian source with side information available only at the decoder
in the form of a noisy version of the source to be encoded. Theoretical models are first established
and derived for calculating distortion-rate functions. Then a few novel practical code implementations are proposed by using the strategy of multi-dimensional nested lattice/trellis coding. By
investigating various lattices in the dimensions considered, analysis is given on how lattice properties affect performance. Also proposed are methods on choosing good sublattices in multiple
dimensions. By introducing scaling factors, the relationship between distortion and scaling factor
is examined for various rates. The best high-dimensional lattice using our scale-rotate method can
achieve a performance less than 1 dB at low rates from the Wyner-Ziv limit; and random nested
ensembles can achieve a 1.87 dB gap with the limit. Moreover, the code design is extended to
incorporate with distributed compressive sensing (DCS). Theoretical framework is proposed and
practical design using nested lattice/trellis is presented for various scenarios. By using nested
trellis, the simulation shows a 3.42 dB gap from our derived bound for the DCS plus Wyner-Ziv
framework
Self-concatenated code design and its application in power-efficient cooperative communications
In this tutorial, we have focused on the design of binary self-concatenated coding schemes with the help of EXtrinsic Information Transfer (EXIT) charts and Union bound analysis. The design methodology of future iteratively decoded self-concatenated aided cooperative communication schemes is presented. In doing so, we will identify the most important milestones in the area of channel coding, concatenated coding schemes and cooperative communication systems till date and suggest future research directions
REGION-BASED ADAPTIVE DISTRIBUTED VIDEO CODING CODEC
The recently developed Distributed Video Coding (DVC) is typically suitable for the
applications where the conventional video coding is not feasible because of its
inherent high-complexity encoding. Examples include video surveillance usmg
wireless/wired video sensor network and applications using mobile cameras etc. With
DVC, the complexity is shifted from the encoder to the decoder.
The practical application of DVC is referred to as Wyner-Ziv video coding (WZ)
where an estimate of the original frame called "side information" is generated using
motion compensation at the decoder. The compression is achieved by sending only
that extra information that is needed to correct this estimation. An error-correcting
code is used with the assumption that the estimate is a noisy version of the original
frame and the rate needed is certain amount of the parity bits. The side information is
assumed to have become available at the decoder through a virtual channel. Due to
the limitation of compensation method, the predicted frame, or the side information, is
expected to have varying degrees of success. These limitations stem from locationspecific
non-stationary estimation noise. In order to avoid these, the conventional
video coders, like MPEG, make use of frame partitioning to allocate optimum coder
for each partition and hence achieve better rate-distortion performance. The same,
however, has not been used in DVC as it increases the encoder complexity.
This work proposes partitioning the considered frame into many coding units
(region) where each unit is encoded differently. This partitioning is, however, done at
the decoder while generating the side-information and the region map is sent over to
encoder at very little rate penalty. The partitioning allows allocation of appropriate
DVC coding parameters (virtual channel, rate, and quantizer) to each region. The
resulting regions map is compressed by employing quadtree algorithm and
communicated to the encoder via the feedback channel. The rate control in DVC is
performed by channel coding techniques (turbo codes, LDPC, etc.). The performance
of the channel code depends heavily on the accuracy of virtual channel model that models estimation error for each region. In this work, a turbo code has been used and
an adaptive WZ DVC is designed both in transform domain and in pixel domain. The
transform domain WZ video coding (TDWZ) has distinct superior performance as
compared to the normal Pixel Domain Wyner-Ziv (PDWZ), since it exploits the
'
spatial redundancy during the encoding. The performance evaluations show that the
proposed system is superior to the existing distributed video coding solutions.
Although the, proposed system requires extra bits representing the "regions map" to be
transmitted, fuut still the rate gain is noticeable and it outperforms the state-of-the-art
frame based DVC by 0.6-1.9 dB.
The feedback channel (FC) has the role to adapt the bit rate to the changing
'
statistics between the side infonmation and the frame to be encoded. In the
unidirectional scenario, the encoder must perform the rate control. To correctly
estimate the rate, the encoder must calculate typical side information. However, the
rate cannot be exactly calculated at the encoder, instead it can only be estimated. This
work also prbposes a feedback-free region-based adaptive DVC solution in pixel
domain based on machine learning approach to estimate the side information.
Although the performance evaluations show rate-penalty but it is acceptable
considering the simplicity of the proposed algorithm.
vii