A data processing method includes: acquiring first image data including pixel values that are arranged consecutively and divided into data blocks, each data block occupying one byte and including at least one pixel value; and compressing, according to at least one compression parameter, at least one data set to be compressed in the first image data into a corresponding compression unit, so as to obtain second image data including the compression unit. The data set to be compressed includes at least two data groups that are arranged consecutively and identical. Each data group includes a single data block or at least two data blocks arranged consecutively. The at least one compression parameter includes a first length configured to represent the number of at least one data block in a data group. The compression unit includes one data group and a second length configured to represent the number of data groups.

A method of processing an immersive video includes classifying each of a plurality of objects included in a view image as one of a first object group and a second object group, acquiring a patch for each of the plurality of objects, and packing patches to generate at least one atlas. In this instance, patches derived from objects belonging to the first object group may be packed in a different region or a different atlas from a region or an atlas of patches derived from objects belonging to the second object group.

A method of processing an immersive video includes classifying each of a plurality of objects included in a view image as one of a first object group and a second object group, acquiring a patch for each of the plurality of objects, and packing patches to generate at least one atlas. In this instance, patches derived from objects belonging to the first object group may be packed in a different region or a different atlas from a region or an atlas of patches derived from objects belonging to the second object group.

A video processing method includes determining, for a conversion between a current block of a video and a bitstream representation of the video, whether to enable a level mapping operation or a level remapping operation based on a rule, wherein the level mapping operation or the level remapping operation includes changing between a first representation of a residual coefficient of the current block and a second representation of the residual coefficient of the current block based on neighboring residual coefficients of the residual coefficient; and performing the conversion by selectively using the level mapping operation or the level remapping operation based on the determining.

A video processing method includes determining, for a conversion between a current block of a video and a bitstream representation of the video, whether to enable a level mapping operation or a level remapping operation based on a rule, wherein the level mapping operation or the level remapping operation includes changing between a first representation of a residual coefficient of the current block and a second representation of the residual coefficient of the current block based on neighboring residual coefficients of the residual coefficient; and performing the conversion by selectively using the level mapping operation or the level remapping operation based on the determining.

An encoder includes circuitry configured to receive a video frame, partition the video frame into a plurality of blocks, determine a respective spatial activity measure for each block in the plurality of blocks and using a transform matrix, encode the video frame using the spatial activity measure. Related apparatus, systems, techniques and articles are also described.

Examples described herein relate to decoding and encoding signals. Certain examples described herein encapsulate custom data that is not signal data within a stream of encoded signal data. The custom data may comprise a wide variety of metadata that annotates the signal data, or provides additional information relating to the signal data. Certain examples described herein encapsulate custom data within a set of transformed coefficient values that represent data derived from a transform operation that forms part of the signal encoding. The encapsulation is may be performed by applying a bit shift operation to coefficient bits representing the set of transformed coefficient values.

A method for identifying stationary regions in frames of a video sequence comprises receiving an encoded version of the video sequence, wherein the encoded version of the video sequence includes an intra-coded frame followed by a plurality of inter-coded frames; reading coding-mode information in the inter-coded frames of the encoded version of the video sequence, wherein the coding-mode information is indicative of blocks of pixels in the inter-coded frames being skip-coded; finding, using the read coding-mode information, one or more blocks of pixels that each was skip-coded in a respective plurality of consecutive frames in the encoded version of the video sequence; and designating each found block of pixels as a stationary region in the respective plurality of consecutive frames.

A deep learning based compression (DLBC) system trains multiple models that, when deployed, generates a compressed binary encoding of an input image that achieves a reconstruction quality and a target compression ratio. The applied models effectively identifies structures of an input image, quantizes the input image to a target bit precision, and compresses the binary code of the input image via adaptive arithmetic coding to a target codelength. During training, the DLBC system reconstructs the input image from the compressed binary encoding and determines the loss in quality from the encoding process. Thus, the models can be continually trained to, when applied to an input image, minimize the loss in reconstruction quality that arises due to the encoding process while also achieving the target compression ratio.

The coding efficiency of scalable video coding is increased by substituting missing spatial intra prediction parameter candidates in a spatial neighborhood of a current block of the enhancement layer by use of intra prediction parameters of a co-located block of the base layer signal. By this measure, the coding efficiency for coding the spatial intra prediction parameters is increased due to the improved prediction quality of the set of intra prediction parameters of the enhancement layer, or, more precisely stated, the increased likelihood, that appropriate predictors for the intra prediction parameters for an intra predicted block of the enhancement layer are available thereby increasing the likelihood that the signaling of the intra prediction parameter of the respective enhancement layer block may be performed, on average, with less bits.