3,550 research outputs found
Distributed video coding for wireless video sensor networks: a review of the state-of-the-art architectures
Distributed video coding (DVC) is a relatively new video coding architecture originated from two fundamental theorems namely, Slepian–Wolf and Wyner–Ziv. Recent research developments have made DVC attractive for applications in the emerging domain of wireless video sensor networks (WVSNs). This paper reviews the state-of-the-art DVC architectures with a focus on understanding their opportunities and gaps in addressing the operational requirements and application needs of WVSNs
Intra-WZ quantization mismatch in distributed video coding
During the past decade, Distributed Video Coding (DVC) has emerged as a new video coding paradigm, shifting the complexity from the encoder-to the decoder-side. This paper addresses a problem of current DVC architectures that has not been studied in the literature so far, that is, the mismatch between the intra and Wyner-Ziv (WZ) quantization processes. Due to this mismatch, WZ rate is spent even for spatial regions that are accurately approximated by the side-information. As a solution, this paper proposes side-information generation using selective unidirectional motion compensation from temporally adjacent WZ frames. Experimental results show that the proposed approach yields promising WZ rate gains of up to 7% relative to the conventional method
Adaptive temporal decimation algorithm with dynamic time window
Published versio
Mesh-based video coding for low bit-rate communications
In this paper, a new method for low bit-rate content-adaptive mesh-based video coding is proposed. Intra-frame coding of this method employs feature map extraction for node distribution at specific threshold levels to achieve higher density placement of initial nodes for regions that contain high frequency features and conversely sparse placement of initial nodes for smooth regions. Insignificant nodes are largely removed using a subsequent node elimination scheme. The Hilbert scan is then applied before quantization and entropy coding to reduce amount of transmitted information. For moving images, both node position and color parameters of only a subset of nodes may change from frame to frame. It is sufficient to transmit only these changed parameters. The proposed method is well-suited for video coding at very low bit rates, as processing results demonstrate that it provides good subjective and objective image quality at a lower number of required bits
Compensating for motion estimation inaccuracies in DVC
Distributed video coding is a relatively new video coding approach, where compression is achieved by performing motion estimation at the decoder. Current techniques for decoder-side motion estimation make use of assumptions such as linear motion between the reference frames. It is only after the frame is partially decoded that some of the errors are corrected. In this paper, we propose a new approach with multiple predictors, accounting for inaccuracies in the decoder-side motion estimation process during the decoding. Each of the predictors is assigned a weight, and the correlation between the original frame at the encoder and the set of predictors at the decoder is modeled at the decoder. This correlation information is then used during the decoding process. Results indicate average quality gains up to 0.4 dB
Distributed coding of endoscopic video
Triggered by the challenging prerequisites of wireless capsule endoscopic video technology, this paper presents a novel distributed video coding (DVC) scheme, which employs an original hash-based side-information creation method at the decoder. In contrast to existing DVC schemes, the proposed codec generates high quality side-information at the decoder, even under the strenuous motion conditions encountered in endoscopic video. Performance evaluation using broad endoscopic video material shows that the proposed approach brings notable and consistent compression gains over various state-of-the-art video codecs at the additional benefit of vastly reduced encoding complexity
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
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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
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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.
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Study and simulation of low rate video coding schemes
The semiannual report is included. Topics covered include communication, information science, data compression, remote sensing, color mapped images, robust coding scheme for packet video, recursively indexed differential pulse code modulation, image compression technique for use on token ring networks, and joint source/channel coder design
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