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082 0 4 _a621.382
_223
100 1 _aRüfenacht, Dominic.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aNovel Motion Anchoring Strategies for Wavelet-based Highly Scalable Video Compression
_h[electronic resource] /
_cby Dominic Rüfenacht.
250 _a1st ed. 2018.
264 1 _aSingapore :
_bSpringer Singapore :
_bImprint: Springer,
_c2018.
300 _aXXIII, 182 p. 92 illus., 62 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSpringer Theses, Recognizing Outstanding Ph.D. Research,
_x2190-5053
500 _aAcceso multiusuario
505 0 _aIntroduction -- Scalable Image and Video Compression -- Temporal Frame Interpolation (TFI) -- Motion-Discontinuity-Aided Motion Field Operations -- Bidirectional Hierarchical Anchoring (BIHA) of Motion -- Forward-Only Hierarchical Anchoring (FOHA) of Motion -- Base-Anchored Motion (BAM) -- Conclusions and Future Directions.
520 _aThis thesis explores the motion anchoring strategies, which represent a fundamental change to the way motion is employed in a video compression system-from a "prediction-centric" point of view to a "physical" representation of the underlying motion of the scene. The proposed "reference-based" motion anchorings can support computationally efficient, high-quality temporal motion inference, which requires half as many coded motion fields as conventional codecs. This raises the prospect of achieving lower motion bitrates than the most advanced conventional techniques, while providing more temporally consistent and meaningful motion. The availability of temporally consistent motion can facilitate the efficient deployment of highly scalable video compression systems based on temporal lifting, where the feedback loop used in traditional codecs is replaced by a feedforward transform.The novel motion anchoring paradigm proposed in this thesis is well adapted to seamlessly supporting "features" beyond compressibility, including high scalability, accessibility, and "intrinsic" frame upsampling. These features are becoming ever more relevant as the way video is consumed continues to shift from the traditional broadcast scenario with predefined network and decoder constraints to interactive browsing of video content via heterogeneous networks.
541 _fUABC ;
_cTemporal ;
_d01/01/2021-12/31/2023.
650 0 _aSignal processing.
650 0 _aImage processing.
650 0 _aSpeech processing systems.
650 0 _aOptical data processing.
650 0 _aMathematics.
650 0 _aVisualization.
650 1 4 _aSignal, Image and Speech Processing.
_0https://scigraph.springernature.com/ontologies/product-market-codes/T24051
650 2 4 _aImage Processing and Computer Vision.
_0https://scigraph.springernature.com/ontologies/product-market-codes/I22021
650 2 4 _aVisualization.
_0https://scigraph.springernature.com/ontologies/product-market-codes/M14034
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9789811082245
776 0 8 _iPrinted edition:
_z9789811082269
776 0 8 _iPrinted edition:
_z9789811340970
830 0 _aSpringer Theses, Recognizing Outstanding Ph.D. Research,
_x2190-5053
856 4 0 _zLibro electrónico
_uhttp://148.231.10.114:2048/login?url=https://doi.org/10.1007/978-981-10-8225-2
912 _aZDB-2-ENG
912 _aZDB-2-SXE
942 _cLIBRO_ELEC
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