MULTI-DISTRIBUTION ENTROPY MODELING OF LATENT FEATURES IN IMAGE AND VIDEO CODING USING NEURAL NETWORKS

MULTI-DISTRIBUTION ENTROPY MODELING OF LATENT FEATURES IN IMAGE AND VIDEO CODING USING NEURAL NETWORKS

Methods, systems, and bitstream syntax are described for the entropy modeling of latent features in image and video coding using a combination of probability density functions. Using high-level syntax elements, an encoder may signal to compliant decoders the multi-distribution entropy model using: t...

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Bibliographische Detailangaben
Hauptverfasser: SHINGALA, Jay Nitin, YIN, Peng, MOHANANCHETTIAR, Arunkumar, MCCARTHY, Sean Thomas
Format: Patent
Sprache:eng
Schlagworte:
ELECTRIC COMMUNICATION TECHNIQUE
ELECTRICITY
PICTORIAL COMMUNICATION, e.g. TELEVISION
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Beschreibung
Zusammenfassung:Methods, systems, and bitstream syntax are described for the entropy modeling of latent features in image and video coding using a combination of probability density functions. Using high-level syntax elements, an encoder may signal to compliant decoders the multi-distribution entropy model using: the number of one or more PDFs being used, an identifier of each PDF being used among a list of available PDFs, the number of PDF parameters in each PDF, and syntax elements indicating which PDF parameters across two or more PDFs being used are being shared.