Advanced heterogeneous video transcoding
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Video transcoding is an essential tool to promote inter-operability
between different video communication systems. This thesis presents
two novel video transcoders, both operating on bitstreams of the cur-
rent H.264/AVC standard. The first transcoder converts H.264/AVC
bitstreams to a Wavelet Scalable Video Codec (W-SVC), while the second targets the emerging High Efficiency Video Coding (HEVC).
Scalable Video Coding (SVC) enables low complexity adaptation
of compressed video, providing an efficient solution for content delivery
through heterogeneous networks. The transcoder proposed here aims at
exploiting the advantages offered by SVC technology when dealing with
conventional coders and legacy video, efficiently reusing information
found in the H.264/AVC bitstream to achieve a high rate-distortion
performance at a low complexity cost. Its main features include new
mode mapping algorithms that exploit the W-SVC larger macroblock
sizes, and a new state-of-the-art motion vector composition algorithm
that is able to tackle different coding configurations in the H.264/AVC
bitstream, including IPP or IBBP with multiple reference frames.
The emerging video coding standard, HEVC, is currently approaching the final stage of development prior to standardization. This thesis
proposes and evaluates several transcoding algorithms for the HEVC
codec. In particular, a transcoder based on a new method that is capable of complexity scalability, trading off rate-distortion performance
for complexity reduction, is proposed. Furthermore, other transcoding solutions are explored, based on a novel content-based modeling
approach, in which the transcoder adapts its parameters based on the
contents of the sequence being encoded.
Finally, the application of this research is not constrained to these
transcoders, as many of the techniques developed aim to contribute
to advance the research on this field, and have the potential to be
incorporated in different video transcoding architectures.
Authors
Peixoto Fernandes da Silva, EduardoCollections
- Theses [3834]