THESIS
2013
xv, 131 pages : illustrations ; 30 cm
Abstract
Video coding is the process of compressing and decompressing a 2D digital
video signal, which is widely used in broadcasting TV, terrestrial TV, video
streaming, video conferencing and DVD applications. The benefits of improving
the coding efficiency are obvious in the sense that it will reduce the bandwidth
for transmitting the compressed signal, save the storage memory size and improve
the visual quality under the same bitrate. To improve the coding efficiency,
rate-distortion optimization techniques are widely used in image and video compression
systems, which are concerned with the task of representing a source
with as few bits as possible, for a given fidelity constraint. In practice, the constrained
rate-distortion optimization problem is formulated as an unconstrained
L...[
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Video coding is the process of compressing and decompressing a 2D digital
video signal, which is widely used in broadcasting TV, terrestrial TV, video
streaming, video conferencing and DVD applications. The benefits of improving
the coding efficiency are obvious in the sense that it will reduce the bandwidth
for transmitting the compressed signal, save the storage memory size and improve
the visual quality under the same bitrate. To improve the coding efficiency,
rate-distortion optimization techniques are widely used in image and video compression
systems, which are concerned with the task of representing a source
with as few bits as possible, for a given fidelity constraint. In practice, the constrained
rate-distortion optimization problem is formulated as an unconstrained
Lagrangian minimization problem, which is used to evaluate the performance of
each possible coding mode.
In this thesis, we address the problems of intra prediction, intra transform
coding and quantization in the traditional 2D video coding framework, and interview
prediction in the 3D video coding framework from the perspective of rate
distortion optimization. First, an edge-based adaptive directional intra prediction
is proposed to reduce the residue energy for edge rich regions. Starting from the
nature of traditional block based intra prediction, the residue characteristics are
experimentally analyzed. It is pointed out that traditional block based intra
prediction fails to predict the edge region with high prediction accuracy. To
solve this problem, an edge model is established within a block and the model
parameters are determined using the rate distortion optimization criteria.
Next, the intra transform coding is investigated. After intra prediction,
residue is formed by subtracting the predictor from the original signal and transform
coding is applied to the residue. To further improve the coding efficiency of
intra transform coding, a rate-distortion cost function is established to estimate
the practical rate-distortion cost. Through minimizing the proposed cost function,
we put forward a novel rate-distortion optimized transform (RDOT) scheme
which allows a set of specially trained transforms to be available to all modes, and
each block can choose its preferred transform to minimize the rate-distortion cost.
The optimization can be solved using the Lloyd-type algorithm (a sequence of
transform optimization and data reclassification alternately) to find the optimal
set of transforms.
Further, we address the scalar quantization in intra frame coding. After transform,
the transformed coefficients are quantized using scaler quantizer. We examine
and analyze the statistical properties of transformed coefficients of different
intra prediction modes, and derive an optimal quantization matrix, such that the
total rate is minimized under a distortion constraint for each mode.
Besides the intra frame coding, the inter-view coding is discussed in the context
of 3D video coding from the perspective of rate distortion optimization.
To improve the coding efficiency of 3D coding systems, view synthesis prediction
(VSP) is proposed as an alternative non-translational disparity compensated predictor.
And it is argued that when we choose the depth derived disparity vector
as the motion vector and motion vector predictor, the lower bound of the Lagrangian
cost is achieved. And this technique is adopted in the 3D video coding
standard 3D-HEVC.
To further increase the usage of VSP, an improved depth coding is proposed
by allowing different quantization parameters (QP) for each block according to
their content characteristics. And the decision of the depth QP is made according
to the rate distortion minimization criteria, where the distortion is measured in
terms of both synthesis distortion and depth coding distortion, rather than depth
coding distortion alone.
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