702 research outputs found
Advanced heterogeneous video transcoding
PhDVideo 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
Overview of MV-HEVC prediction structures for light field video
Light field video is a promising technology for delivering the required six-degrees-of-freedom for natural content in virtual reality. Already existing multi-view coding (MVC) and multi-view plus depth (MVD) formats, such as MV-HEVC and 3D-HEVC, are the most conventional light field video coding solutions since they can compress video sequences captured simultaneously from multiple camera angles. 3D-HEVC treats a single view as a video sequence and the other sub-aperture views as gray-scale disparity (depth) maps. On the other hand, MV-HEVC treats each view as a separate video sequence, which allows the use of motion compensated algorithms similar to HEVC. While MV-HEVC and 3D-HEVC provide similar results, MV-HEVC does not require any disparity maps to be readily available, and it has a more straightforward implementation since it only uses syntax elements rather than additional prediction tools for inter-view prediction. However, there are many degrees of freedom in choosing an appropriate structure and it is currently still unknown which one is optimal for a given set of application requirements. In this work, various prediction structures for MV-HEVC are implemented and tested. The findings reveal the trade-off between compression gains, distortion and random access capabilities in MVHEVC light field video coding. The results give an overview of the most optimal solutions developed in the context of this work, and prediction structure algorithms proposed in state-of-the-art literature. This overview provides a useful benchmark for future development of light field video coding solutions
JND-Based Perceptual Video Coding for 4:4:4 Screen Content Data in HEVC
The JCT-VC standardized Screen Content Coding (SCC) extension in the HEVC HM
RExt + SCM reference codec offers an impressive coding efficiency performance
when compared with HM RExt alone; however, it is not significantly perceptually
optimized. For instance, it does not include advanced HVS-based perceptual
coding methods, such as JND-based spatiotemporal masking schemes. In this
paper, we propose a novel JND-based perceptual video coding technique for HM
RExt + SCM. The proposed method is designed to further improve the compression
performance of HM RExt + SCM when applied to YCbCr 4:4:4 SC video data. In the
proposed technique, luminance masking and chrominance masking are exploited to
perceptually adjust the Quantization Step Size (QStep) at the Coding Block (CB)
level. Compared with HM RExt 16.10 + SCM 8.0, the proposed method considerably
reduces bitrates (Kbps), with a maximum reduction of 48.3%. In addition to
this, the subjective evaluations reveal that SC-PAQ achieves visually lossless
coding at very low bitrates.Comment: Preprint: 2018 IEEE International Conference on Acoustics, Speech and
Signal Processing (ICASSP 2018
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