Abstract: Entropy coding a sequence of transform coefficients includes determining a predictor value corresponding to a transform coefficient, selecting a probability model from a set of pre-defined probability models based on the predictor value, and entropy coding a symbol associated with the transform coefficient using the selected probability model. The predictor value can be calculated based on a previous predictor value used for coding an immediately preceding symbol associated with an immediately preceding transform coefficient of the sequence of the transform coefficients. The predictor value can be further calculated based on the immediately preceding symbol.

Abstract: Bypass decoding by an arithmetic decoder is disclosed. A request to decode a number of binary bits from a compressed bitstream is received. Each of the binary bits is equi-probable. The arithmetic decoder maintains an offset and a range. A decoding range is established based on the range. The binary values for the binary bits are decoded by: for each binary bit of the binary bits, performing the steps of comparing the offset to a midpoint of the decoding range to determine a binary value for the each binary bit, where the binary value is decoded from the compressed bitstream; conditionally updating the midpoint based on the comparing; and halving the midpoint so that an equi-probability is maintained for decoding a next binary bit subsequent to the each binary bit. The binary values of the binary bits are then provided.

Abstract: A data-driven intra-prediction mode is identified. Features are extracted from samples neighboring a current block. The features are processed based on the data-driven intra-prediction mode to obtain processed features. The processed features are converted into a matrix. A prediction block for the current block is generated based on the matrix. Extracting the features from the samples neighboring the current block includes selecting the samples at predefined fixed locations from neighboring reconstructed regions and deriving the features from the selected samples.

Abstract: An electromagnetic tracking system includes an adjustable source of electricity, a magneto-resistive (MR) sensor coupled to the adjustable source of electricity and configured to couple to a device for tracking a position of the device, and a controller coupled to the adjustable source of electricity and the MR sensor to adjust an amount of electricity provided to the MR sensor by the adjustable source of electricity. The electromagnetic tracking system is configured to track MR sensors and coil-based sensors simultaneously using one or more input channels on the controller.

Abstract: Entropy coding a sequence of syntax elements is described where an observation for a syntax element of the sequence is determined, and the observation is arithmetic coded using the probability model. Thereafter, the probability model is updated using a time-variant update rate to produce an updated probability model. Updating the probability model includes regularizing one or more probability values of the probability model so no probability of the updated probability model is below a defined minimum resolution. As a result, the use of a minimum probability value during the arithmetic coding, which can distort probability model, may be omitted.

Abstract: Entropy coding a sequence of transform coefficients includes determining a predictor value corresponding to a transform coefficient, selecting a probability model from a set of pre-defined probability models based on the predictor value, and entropy coding a symbol associated with the transform coefficient using the selected probability model. The predictor value can be calculated based on a previous predictor value used for coding an immediately preceding symbol associated with an immediately preceding transform coefficient of the sequence of the transform coefficients. The predictor value can be further calculated based on the immediately preceding symbol.

Abstract: An apparatus for encoding an image block includes a processor that presents, to a machine-learning model, the image block, obtains the partition decision for encoding the image block from the model, and encodes the image block using the partition decision. The model is trained to output a partition decision for encoding the image block by using training data for a plurality of training blocks as input, the training data including for a training block, partition decisions for encoding the training block, and, for each partition decision, a rate-distortion value resulting from encoding the training block using the partition decision. The model is trained using a loss function combining a partition loss function based upon a relationship between the partition decisions and respective predicted partitions, and a rate-distortion cost loss function based upon a relationship between the rate-distortion values and respective predicted rate-distortion values.

Abstract: An apparatus for decoding a current block includes a processor that is configured to obtain a transform class of a transform type used for decoding a transform block of the current block; select, based on the transform class, a template for coding a value related to a transform coefficient at a row and a column of the transform block; obtain, using the template, an index of a probability distribution in a table of probability distributions; and decode, from a compressed bitstream, the value using the probability distribution.

Abstract: An apparatus for encoding an image block includes a processor that presents, to a machine-learning model, the image block, obtains the partition decision for encoding the image block from the model, and encodes the image block using the partition decision. The model is trained to output a partition decision for encoding the image block by using training data for a plurality of training blocks as input, the training data including for a training block, partition decisions for encoding the training block, and, for each partition decision, a rate-distortion value resulting from encoding the training block using the partition decision. The model is trained using a loss function combining a partition loss function based upon a relationship between the partition decisions and respective predicted partitions, and a rate-distortion cost loss function based upon a relationship between the rate-distortion values and respective predicted rate-distortion values.

Abstract: A method for coding a frame of a video stream includes selecting a first initial probability distribution for coding at least a first portion of the frame; updating, to obtain an updated first initial probability distribution and using backward adaptivity, the first initial probability distribution while coding the first portion of the frame; mapping the updated first initial probability distribution to a second initial probability distribution; and coding a second portion of the frame using the second initial probability distribution as an initial probability distribution. The first values of the first initial probability distribution are described using M bits, wherein M is a first positive integer. Second values of the updated first initial probability distribution are described using N bits, where N is a second positive integer that is greater than M. Third values of the second initial probability distribution are described using M bits.

Abstract: Coding a current block using a directional intra-prediction mode is described. A filter to apply to reference pixels peripheral to the current block is determined using a prediction angle of the intra-prediction mode and a size of the current block. The reference pixels are filtered using the filter to generate modified reference pixels, and a prediction block is generated for the current block using the intra-prediction mode and the modified reference pixels.

Abstract: An apparatus for decoding a current block includes a processor that is configured to obtain a transform class of a transform type used for decoding a transform block of the current block; select, based on the transform class, a template for coding a value related to a transform coefficient at a row and a column of the transform block; obtain, using the template, an index of a probability distribution in a table of probability distributions; and decode, from a compressed bitstream, the value using the probability distribution.

Abstract: An apparatus includes a memory and a processor. The processor is configured to execute instructions stored in the memory to obtain a transform type for decoding a transform block for the current block; select, based on the transform type, a template for coding a value of a non-zero map; select, based on the template, a context for entropy decoding the value of the non-zero map; and decode the value of the non-zero map based on the context. The non-zero map indicates which coefficients of the transform block have non-zero values. A method includes obtaining a transform class for coding a transform block for the current block, wherein the transform class corresponding to a transform type and a direction; selecting, based on the transform class, a coding context for coding a value of a non-zero map; and coding the value of the non-zero map based on the coding context.

Abstract: A fugitive emissions packing set is provided. The packing set a top ring and a bottom ring made from a fluoropolymer that includes a filler that enhances the mechanical and/or dimensional stability of the ring, as compared to unfilled fluoropolymer. The intermediate rings are formed from an essentially pure fluoropolymer. The top, bottom, or intermediate rings may include a metal insert in any combination.

Abstract: A method for coding a current block using an intra-prediction mode includes defining a mapping from available intra-prediction modes to intra-prediction classes; determining, using the mapping, a first intra-prediction class of a first intra-prediction mode used for decoding a first neighboring block of the current block; determining, using the mapping, a second intra-prediction class of a second intra-prediction mode used for decoding a second neighboring block of the current block; using the first intra-prediction class and the second intra-prediction class as indices into a list of available context models to select a context model for coding the intra-prediction mode; and coding the intra-prediction mode using the context model. A first number of the intra-prediction classes is smaller than a second number of the available intra-prediction modes. each class is an ordinal value, and each available intra-prediction mode uniquely maps to one class of the intra-prediction classes.

Abstract: A method for coding a frame of a video stream includes selecting a first initial probability distribution for coding at least a first portion of the frame; updating, to obtain an updated first initial probability distribution and using backward adaptivity, the first initial probability distribution while coding the first portion of the frame; mapping the updated first initial probability distribution to a second initial probability distribution; and coding a second portion of the frame using the second initial probability distribution as an initial probability distribution. The first values of the first initial probability distribution are described using M bits, wherein M is a first positive integer. Second values of the updated first initial probability distribution are described using N bits, where N is a second positive integer that is greater than M. Third values of the second initial probability distribution are described using M bits.

Abstract: Efficient noise reduction coding may include generating, by a processor, an encoded frame by encoding an input video frame. Encoding the input frame includes determining an estimated noise level for the input video frame, determining a minimum quantization parameter level based on the estimated noise level for the input video frame, determining a quantization parameter value for encoding the input frame such that the quantization parameter value is at least the minimum quantization parameter level, obtaining the encoded frame by encoding the input frame in accordance with the quantization parameter level, including the encoded frame in an output bitstream, and outputting the output bitstream.