THESIS
2014
xii, 97 pages : illustrations ; 30 cm
Abstract
High Efficiency Video Coding (HEVC) is the next generation video coding standard,
which has been established jointly by the ITU-T Video Coding Experts
Group and the ISO/IEC Moving Pictures Experts Group (MPEG) standardization
organizations, known as the Joint Collaborative Team on Video Coding
(JCT-VC). It is designed to reduce the bit-rate by half, with equal perceptual
video quality compared to existing video coding standards. With the first draft
of HEVC finalized in early 2013, several extensions, including range extensions,
scalable extensions and 3D video extensions, have been discussed to fulfill various
requirements of a broader range of applications.
In this thesis, we firstly proposed to use a CU (coding block) level spatially
adaptive KLT-based color transform, wh...[
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High Efficiency Video Coding (HEVC) is the next generation video coding standard,
which has been established jointly by the ITU-T Video Coding Experts
Group and the ISO/IEC Moving Pictures Experts Group (MPEG) standardization
organizations, known as the Joint Collaborative Team on Video Coding
(JCT-VC). It is designed to reduce the bit-rate by half, with equal perceptual
video quality compared to existing video coding standards. With the first draft
of HEVC finalized in early 2013, several extensions, including range extensions,
scalable extensions and 3D video extensions, have been discussed to fulfill various
requirements of a broader range of applications.
In this thesis, we firstly proposed to use a CU (coding block) level spatially
adaptive KLT-based color transform, which achieves optimal energy compaction.
The proposed algorithm transforms the current color space into a new color space,
whose color channels are less correlated so as to improve the coding performance.
The transform matrix is estimated from the reconstructed pixels from neighboring
blocks. The adaptive transform tends to give color components with variable
bit depth. As minimal change to the existing HEVC is desirable, all color components
need to have 8-bit bit depth. Thus we also propose a novel dynamic
range adjustment algorithm so that the existing HEVC Range Extension can be
applied almost directly.
Secondly, while rate-distortion (RD) optimization is well known to give optimal
results, we propose two modifications to the RD cost function especially
for the proposed adaptive KLT-based color transform so as to achieve superior performance. The first modification is to perform color adaptive scaling, which
translates to using three color adaptive Lagrange multipliers. The second modification
is to include in the cost function a term that considers the cross-color
correlation among the distortions in different colors.
Thirdly, we propose a palette-based compound image compression algorithm
for artificial screen contents, such as those in video games and computer remote
desktops. Screen content usually contains sharp edges, which often can not be
coded efficiently with traditional transform coding. Palette-based methods use a
palette plus index map technique to represent such blocks. To reduce the overhead
in coding the locally adaptive color palette, the proposed algorithm uses a global
color palette template to predict the local palette.
Finally, in this thesis, the color characteristic among different bit streams,
which are encoded from same video source but different quality levels, is investigated
and a simplified generalized residual prediction (GRP) algorithm is
proposed in scalable extensions of HEVC. The prediction of the current block
in the enhancement layer is jointly predicted from the enhancement layer and
also the base layer. Also, by studying the properties of merge mode and residual
characteristics, the proposed algorithms simplify the coding process by only
testing the GRP in merge mode. Experimental results show that the proposed
algorithms improve the coding performance of the extensions in HEVC effectively.
Besides color characteristic coding in HEVC, an image deblocking algorithm
using convex optimization techniques is also presented.
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