An encoding device comprises: a transformer/quantizer configured to perform a transform process and a quantization process on a residual signal that represents a difference between an encoding-target block and a prediction block obtained by predicting the encoding-target block; an inverse quantizer/inverse transformer configured to restore the residual signal by performing an inverse quantization process and an inverse transform process on transform coefficients obtained by the transformer/quantizer; a combiner configured to reconstruct the encoding-target block by combining the restored residual signal and the prediction block; a deblocking filter configured to perform a filter process on a boundary between two blocks including the reconstructed block and a block adjacent to the reconstructed block; and a filter controller configured to control the deblocking filter, based on a type of the transform process applied with respect to the two blocks.

An encoding device comprises: a transformer/quantizer configured to perform a transform process and a quantization process on a residual signal that represents a difference between an encoding-target block and a prediction block obtained by predicting the encoding-target block; an inverse quantizer/inverse transformer configured to restore the residual signal by performing an inverse quantization process and an inverse transform process on transform coefficients obtained by the transformer/quantizer; a combiner configured to reconstruct the encoding-target block by combining the restored residual signal and the prediction block; a deblocking filter configured to perform a filter process on a boundary between two blocks including the reconstructed block and a block adjacent to the reconstructed block; and a filter controller configured to control the deblocking filter, based on a type of the transform process applied with respect to the two blocks.

Image data encoding apparatus, comprises an entropy encoder configured to selectively encode data items representing image data so as to generate encoded binarized symbols of successive output data units; the entropy encoder being configured to generate an output data stream subject to a constraint defining an upper limit to the number of binarized symbols that may be expressed by any individual output data unit relative to the size in bytes of that output data unit, in which the entropy encoder is configured to provide padding data, for each output data unit which does not meet the constraint, so as to increase the size in bytes of that output data unit in order to meet the constraint; the apparatus comprising: an attribute detector configured to detect an encoding attribute applicable to a given output data unit; and a selector configured to select, in response to the detected encoding attribute, a constraint, for use with the given output data unit, from two or more candidate constraints.

A method and apparatus for variable rate compression with a conditional autoencoder is herein provided. According to one embodiment, a method for compression includes receiving a first image and a first scheme as inputs for an autoencoder network; determining a first Lagrange multiplier based on the first scheme; and using the first image and the first Lagrange multiplier as inputs, computing a second image from the autoencoder network. The autoencoder network is trained using a plurality of Lagrange multipliers and a second image as training inputs.

Apparatus and methods for implementing a real-time Versatile Video Coding (VVC) decoder use multiple threads to address the limitation with existing parallelization techniques and fully utilizes the available CPU computation resource without compromising on the coding efficiency. The proposed Multi-threaded (MT) framework uses CTU level parallel processing techniques without compromising on the memory bandwidth. Picture level parallel processing separates the sequence into temporal levels by considering the picture's referencing hierarchy. Embodiments are provided using various optimization techniques to achieve real-time VVC decoding on heterogenous platforms with multi-core CPUs, for those bitstreams generated using a VVC reference encoder with a default configuration.

Entropy coding a sequence of symbols is described. A first probability model for entropy coding is selected. At least one symbol of the sequence is coded using a probability determined using the first probability model. The probability according to the first probability model is updated with an estimation of a second probability model to entropy code a subsequent symbol. The combination may be a fixed or adaptive combination.

Entropy coding a sequence of symbols is described. A first probability model for entropy coding is selected. At least one symbol of the sequence is coded using a probability determined using the first probability model. The probability according to the first probability model is updated with an estimation of a second probability model to entropy code a subsequent symbol. The combination may be a fixed or adaptive combination.

A video decoding method performed by a video decoding apparatus, according to the present document, comprises: parsing number information about the number of slices of which heights are explicitly signaled in a tile of a current picture from a bitstream; parsing height information about the heights of slices of which heights are explicitly signaled from the bitstream based on the number information; deriving the number of slices in the tile based on the number information and the height information; and decoding the current picture based on the slices in the tile, wherein the height information includes the same number of syntax elements as a value of the number information, and based on the value of the number information being n, the heights of a 0th slice to an n-1th slice in the tile may be derived based on the syntax elements.

A video decoding method performed by a video decoding apparatus, according to the present document, comprises: parsing number information about the number of slices of which heights are explicitly signaled in a tile of a current picture from a bitstream; parsing height information about the heights of slices of which heights are explicitly signaled from the bitstream based on the number information; deriving the number of slices in the tile based on the number information and the height information; and decoding the current picture based on the slices in the tile, wherein the height information includes the same number of syntax elements as a value of the number information, and based on the value of the number information being n, the heights of a 0th slice to an n-1th slice in the tile may be derived based on the syntax elements.

The technology of this application relates to an entropy encoding method that includes obtaining base layer information of a to-be-encoded picture block, where the base layer information corresponds to M samples in the picture block, and M is a positive integer, obtaining K elements corresponding to enhancement layer information of the picture block, where the enhancement layer information corresponds to N samples in the picture block, both K and N are positive integers, and N≥M, inputting the base layer information into a neural network to obtain K groups of probability values, where the K groups of probability values correspond to the K elements, and any group of probability values is for representing probabilities of a plurality of candidate values of a corresponding element, and performing entropy encoding on the K elements based on the K groups of probability values.