The present technology relates to a coding device, a coding method, a decoding device, a decoding method, and a program capable of improving coding efficiency.

The coding device includes a time-frequency transform section that performs time-frequency transform using a transform window on an audio signal, and a coding section that performs Huffman coding on frequency spectrum information obtained by the time-frequency transform in a case in which a transform window length of the transform window is changed over from a small transform window length to a large transform window length, and that performs arithmetic coding on the frequency spectrum information in a case in which the transform window length of the transform window is not changed over from the small transform window length to the large transform window length. The present technology is applicable to a coding device and a decoding device.

Methods and devices for coding point clouds using direct coding mode to code coordinates of a point within a sub-volume associated with a current node instead of a pattern of occupancy for child nodes. Eligibility for use of direct coding is based on occupancy data from another node. If eligible, then a flag is represented in the bitstream to signal whether direct coding is applied to points in the sub-volume or not.

An apparatus comprising: circuitry configured to classify a signal; and circuitry configured to control saving of the signal to a memory with a conditional resolution, wherein a signal that is classified as anomalous is saved at higher resolution as a higher resolution signal and a signal that is not classified as anomalous is saved at lower resolution as a lower resolution signal or is not saved.

An image compression method and an image compressor are provided. The image compression method compresses the image data based on the fixed-length code (FLC) to generate the compressed data, and includes the following steps: determining whether a characteristic value of the image data meets a condition; encoding only the luminance component of the image data to generate the compressed data when the characteristic value meets the condition; encoding the luminance and chrominance components of the image data to generate the compressed data when the characteristic value does not meet the condition; and storing the compressed data.

Apparatuses, methods, systems, and program products are disclosed for compression and distribution of meteorological data using machine learning. An apparatus includes a processor and a memory that stores code executable by the processor to receive a raw meteorological data set for a time frame, the raw meteorological data set comprising a plurality of dimensions. The code is executable by the processor to compress the raw meteorological data set using a machine learning encoding model to create an encoded meteorological data set that has a storage size that is smaller than a storage size of the raw meteorological data set, wherein the encoded meteorological data set can be decoded to create a decoded meteorological data set that is substantially similar to the raw meteorological data set. The code is executable by the processor to make the encoded meteorological data set accessible to one or more end users.

There is provided with a data processing apparatus. An acquisition unit acquires feature plane data of a layer included in a neural network. A control unit outputs a first control signal corresponding to the layer for controlling first compression processing and a second control signal corresponding to the layer for controlling second compression processing. A first compression unit performs the first compression processing corresponding to the first control signal on the feature plane data. A second compression unit performs the second compression processing corresponding to the second control signal on the feature plane data after the first compression processing. A type of processing of the second compression processing is different from the first compression processing.

Aspects of dynamic data compression selection are presented. In an example method, as uncompressed data chunks of a data stream are compressed, at least one performance factor affecting selection of one of multiple compression algorithms for the uncompressed data chunks of the data stream may be determined. Each of the multiple compression algorithms may facilitate a different expected compression ratio. One of the multiple compression algorithms may be selected separately for each uncompressed data chunk of the data stream based on the at least one performance factor. Each uncompressed data chunk may be compressed using the selected one of the multiple compression algorithms for the uncompressed data chunk.

A data encoding system includes a non-transitory memory, a processor, a digital-to-analog converter (DAC) and a transmitter. The non-transitory memory stores a predetermined file size threshold. The processor is in operable communication with the memory, and is configured to receive data. The processor detects a file size associated with the data. When the file size is below the predetermined file size threshold, the processor compresses the data using a variable length codeword (VLC) encoder. When the file size is not below the predetermined file size threshold, the processor compresses the data, using a hash table algorithm. The DAC is configured to receive a digital representation of the compressed data from the processor and convert the digital representation of the compressed data into an analog representation of the compressed data. The transmitter is coupled to the DAC and configured to transmit the analog representation of the compressed data.

Block compression schemes used for image compression are susceptible to generating image blocks having redundant bit sets (i.e. a redundant bit combination), where one of the bit sets in the block is not meaningfully different from the other bit set in the block. As a result, one of the bit sets will be meaningless to a decompression scheme used to decompress the image and thus will not contribute to improving a quality of the decompressed image. The present disclosure provides a technique to exploit redundant bit combinations in a compressed representation of an image, including to exploit more than just the simple case of bit sets that are identical. Exploiting a redundant bit combination will allow an otherwise meaningless bit set to be used for some other discriminating purpose, which can allow for a higher image quality after decompression.

A method performed by a network node (110) is described herein. The method is for managing compression of information to be transmitted by a transmitting device (130) 5 in a set of packets. The network node (110) determines (304) whether or not to apply a first compression algorithm to the information comprised in the set of packets. The determining (304) is based on at least one of: i) a compression efficiency of the first compression algorithm applied to a first information comprised in a first set of packets, and ii) a computational complexity of the first algorithm. The information is a second 10 information and the set of packets is a second set of packets. Each of the first and the second set of packets comprise at least one packet. The network node (110) then initiates (305) providing, based on a result of the determination, an indication of the result to the transmitting device (130).