Fraunhofer-gesellschaft Zur F&#xf6;rderung Der Angewandten Forschung E. V.

Fraunhofer-gesellschaft Zur Foerderung Der Angewandten Forschung E.v.

Fraunhofer-gesellschaft Zur F&#xd6;rderung Der Angewandten Forschung E.v.

Björn Stallenberger

Thomas Wiegand

Detlev Marpe

Heiko Schwarz

Philipp Helle

Philipp Merkle

Jonathan Pfaff

Tobias Hinz

Mischa Siekmann

Martin Winken

Michael Schäfer

Benjamin Bross

Adam Wieckowski

Wojciech Samek

Stephan Kaltenstadler

Roman Rischke

Michael Schafer

An apparatus includes an encoder, which receives image or video data, encodes the data and provides a bitstream. The encoder includes a CABAC encoder, which receives a binary valued syntax element associated with a block of the data to be encoded, and encodes, using a selected context model, the syntax element into coded bits for the bitstream. The syntax element includes a tool flag indicating whether or not certain coding tool is employed when encoding a block of the data. For a block of the data which exhibits an aspect ratio larger than 2 and for a block of the data which exhibits an aspect ratio less than or equal to 2, and to which blocks the certain coding tool is applicable, first and second context models for encoding the tool flag are selected from a group of one or more first and second context models, respectively.

Use-case driven context model selection for hybrid video coding tools

An apparatus configured to select a predetermined intra prediction mode out of a plurality of intra-prediction modes which includes a first set of intra-prediction modes and a second set of matrix-based intra-prediction modes. The apparatus is configured to select a subset of one or more secondary transforms dependent on the predetermined intra prediction mode so that the subset is nonempty in case of the predetermined intra prediction mode being contained in the first set of intra-prediction modes or in the second set of matrix-based intra-prediction modes. The apparatus is configured to derive a transformed version of a prediction residual for a predetermined block, which is related to a spatial domain version of the prediction residual of the predetermined block via a transform defined by a concatenation of a primary transform and a predetermined secondary transform out of the subset of secondary transforms.

Coding using matrix based intra-prediction and secondary transforms

A method for decoding a predetermined block of a picture using intra-prediction by reading, for each of predetermined intra-prediction blocks, from a data stream, a mode index identifying a matrix-based intra-prediction mode is disclosed. Samples of each predetermined intra-prediction block are predicted by computing a matrix-vector product between an input vector derived from reference samples and a prediction matrix associated with the identified matrix-based intra-prediction mode (k)—and associating components of an output vector obtained by the matrix-vector product onto sample positions of the predetermined block. Further predetermined intra-predicted blocks of the picture are predicted to obtain a prediction signal. A transformation flag is decoded from the data stream using context adaptive binary arithmetic coding, and a prediction residual is decoded and re-transformed using a reverse transformation based on the transformation flag to obtain a prediction residual signal. The prediction residual signal is used to correct the prediction signal.

Efficient implementation of matrix-based intra-prediction

A block-based decoder is configured to partition a picture of more than one color component and of a color sampling format, according to which each color component is equally sampled, into blocks using a partitioning scheme in which the picture is equally partitioned with respect to each color component. A first color component is decoded in units of the blocks with selecting, for each of intra-predicted first color component blocks, one out of a first set of intra-prediction modes. The first set comprises matrix-based intra prediction modes according to each of which a block inner is predicted by deriving a sample value vector out of neighboring reference samples, computing a matrix-vector product between the sample value vector and a prediction matrix associated with the respective matrix-based intra prediction mode to obtain a prediction vector, and predicting samples in the block inner on the basis of the prediction vector.

MIP for all channels in the case of 4:4:4-chroma format and of single tree

Techniques for block wise encoding and decoding may be applied to encoders, decoders, and methods for encoding or decoding. In one example, there is provided a technique to decode or encode a predetermined block of the picture by assigning, based on a first signalization in the data stream, the predetermined block to a first set or a second set; sorting the assigned set of intra-prediction modes according to intra-prediction modes used for neighboring blocks, neighboring the predetermined block, to obtain a list of intra prediction modes; deriving, for the predetermined block, from the data stream, an index into the list of intra prediction modes; and predicting the predetermined block using an intra prediction mode onto which the index points. The decoder or encoder, if the assigned set is the first set of intra-prediction modes, in sorting the assigned set, uses a second mapping which maps each intra-prediction mode of the second set of prediction modes onto a representative one in the first set of intra-prediction modes.

Affine linear weighted intra predictions

An apparatus for block-wise decoding a picture from a data stream and/or encoding a picture into a data stream, the apparatus supporting at least one intra-prediction mode according to which the intra-prediction signal for a block of a predetermined size of the picture is determined by applying a first template of samples which neighbours the current block onto a neural network. The apparatus may be configured, for a current block differing from the predetermined size, to:

Intra-prediction mode using downsampling for block-wise picture coding

Apparatus for decoding a predetermined block () of a picture using intra-prediction, configured to read, from the data stream (), a mode index (), the mode index pointing to one out of a list () of matrix-based intra-prediction modes. Additionally, the apparatus is configured to predict samples () of the predetermined block () by computing a matrix-vector product () between an input vector () derived from reference samples () in a neighborhood of the predetermined block () and a prediction matrix () associated with the matrix-based intra-prediction mode (k) pointed to by the mode index () and associating components () of an output vector () obtained by the matrix vector product () onto sample positions () of the predetermined block. For each matrix-based intra-prediction mode, all entries of the prediction matrix () associated with the respective matrix-based intra-prediction mode are represented by a fixed point representation of a predetermined bit-depth, the predetermined bit-depth being equal for the matrix-based intra-prediction modes. Furthermore, the apparatus is configured to, for each matrix-based infra-prediction mode, compute the matrix vector product () between the input vector () and the prediction matrix () associated with the respective matrix-based infra-prediction mode (k) by performing, for each component of the output vector, a right shift at a number of bits which is equal for the matrix-based intra-prediction modes.

Matrix based intra prediction with mode-global settings

A method, computer program, and apparatus for decoding a predetermined block of a picture using intra-prediction by reading, for each of predetermined intra-prediction blocks, from a data stream, a mode index identifying a matrix-based intra-prediction mode. Samples of each predetermined intra-prediction block are predicted by computing a matrix-vector product between an input vector derived from reference samples and a prediction matrix associated with the identified matrix-based intra-prediction mode (k) and associating components of an output vector obtained by the matrix-vector product onto sample positions of the predetermined block. Further predetermined intra-predicted blocks of the picture are predicted to obtain a prediction signal. A transformation flag is decoded from the data stream using context adaptive binary arithmetic coding, and a prediction residual is decoded and re-transformed using a reverse transformation based on the transformation flag to obtain a prediction residual signal. The prediction residual signal is used to correct the prediction signal.

An apparatus includes an encoder, which receives image or video data, encodes the data and provides a bitstream representing the data. The encoder includes a CABAC encoder, which receives a binary valued syntax element associated with a block of the data to be encoded, and encodes, using a selected context model, the syntax element into coded bits for the bitstream. The syntax element includes a tool flag indicating whether or not certain coding tool, like linear weighted intra prediction, is employed when encoding a block of the data. For a block of the data which exhibits an aspect ratio larger than 2 and for a block of the data which exhibits an aspect ratio less than or equal to 2, and to which blocks the certain coding tool is applicable, first and second context models for encoding the tool flag are selected from a group of one or more first and second context models, respectively.

There are disclosed techniques for block wise encoding and decoding. The techniques may be applied to encoders, decoders, and methods for encoding and/or decoding. In one example, there is provided a technique to decode (resp. decode) a predetermined block of the picture by The decoder (resp. encoder), if the assigned set is the first set of intra-prediction modes, in sorting the assigned set, uses a second mapping which maps each intra-prediction mode of the second set of prediction modes onto a representative one in the first set of intra-prediction modes.

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Berlin, Germany

Björn Stallenberger