A decoder includes circuitry configured to receive a bitstream identify, in the bitstream, a current frame, wherein the current frame includes a plurality of regions, detect, in the bitstream, an indication that a first region is encoded according to a lossless encoding protocol and another region is encoded according to a lossy encoding protocol, and decode the current frame, wherein decoding the current frame further comprises decoding the first region using a lossless decoding protocol corresponding to the lossless encoding protocol.

Techniques are disclosed relating to data compression. In some embodiments, compression circuitry determines, at least partially in parallel for multiple different lossless compression techniques, a number of bits needed to represent a least compressible pixel, using that technique, in a set of pixels being compressed. The compression techniques may include neighbor, origin, and gradient techniques, for example. The compression circuitry may select one of the compression techniques based on the determined numbers of bits for the multiple compression techniques and corresponding header sizes. In some embodiments, the compression circuitry determines, for multiple regions of pixels in the set of pixels, for ones of the compression techniques, a region number of bits needed to represent a least compressible pixel, using that technique. The selection of a compression technique may be further based on region numbers of bits.

A computer-implemented method for improving compression of predictive models includes generating an unlabeled simulated data set by expanding an initial data set, and generating a labeled data set by predicting the unlabeled, simulated data set using a complex model to output a plurality of labels. The method also includes training a relatively simple neural network using the labeled data set.

A decoder includes circuitry configured to receive a bitstream identify, in the bitstream, a current frame, wherein the current frame includes a first region and a third region, detect, in the bitstream, an indication that the first region is encoded according to a lossless encoding protocol, and decode the current frame, wherein decoding the current frame further comprises decoding the first region using a lossless decoding protocol corresponding to the lossless encoding protocol.

The present invention relates to a compressed sensing apparatus for compressed sensing of a set function consisting of a plurality of input sets containing a group of data. The apparatus includes: a plurality of sensing units acquiring a group of sampling data representing a plurality of sampling sets selected out of the plurality of input sets; a compression and computation unit enabling a compression to the group of data based on the group of sampling data in accordance with a Fourier basis set generated on the basis of the plurality of input sets and sampling sets, and a computation to compute a Fourier coefficient set based on a sparse regression technique which is in relation with the Fourier basis set; and a reconstruction unit predicting the group of data based on the Fourier coefficient set.

A method, computer program, and computer system is provided for point cloud coding. The method includes receiving, from a bitstream, data corresponding to a point cloud; reconstructing, based on the data, a first attribute value of a first duplicate point from among a plurality of duplicate points corresponding to a single geometry position; obtaining at least one prediction residual corresponding to at least one remaining attribute value of at least one remaining duplicate point from among the plurality of duplicate points; reconstructing the at least one remaining attribute value based on the reconstructed first attribute and the at least one prediction residual; and decoding the data corresponding to the point cloud based on the reconstructed first attribute value and the reconstructed at least one remaining attribute value.

The present invention relates to a compressed sensing apparatus for compressed sensing of a set function consisting of a plurality of input sets containing a group of data. The apparatus includes: a plurality of sensing units acquiring a group of sampling data representing a plurality of sampling sets selected out of the plurality of input sets; a compression and computation unit enabling a compression to the group of data based on the group of sampling data in accordance with a Fourier basis set generated on the basis of the plurality of input sets and sampling sets, and a computation to compute a Fourier coefficient set based on a sparse regression technique which is in relation with the Fourier basis set; and a reconstruction unit predicting the group of data based on the Fourier coefficient set.

Techniques are disclosed relating to data compression. In some embodiments, compression circuitry determines, at least partially in parallel for multiple different lossless compression techniques, a number of bits needed to represent a least compressible pixel, using that technique, in a set of pixels being compressed. The compression techniques may include neighbor, origin, and gradient techniques, for example. The compression circuitry may select one of the compression techniques based on the determined numbers of bits for the multiple compression techniques and corresponding header sizes. In some embodiments, the compression circuitry determines, for multiple regions of pixels in the set of pixels, for ones of the compression techniques, a region number of bits needed to represent a least compressible pixel, using that technique. The selection of a compression technique may be further based on region numbers of bits.

A decoder includes circuitry configured to receive a bitstream identify, in the bitstream, a current frame, wherein the current frame includes a first region and a third region, detect, in the bitstream, an indication that the first region is encoded according to a lossless encoding protocol, and decode the current frame, wherein decoding the current frame further comprises decoding the first region using a lossless decoding protocol corresponding to the lossless encoding protocol.

Techniques are provided for compression of log data using field types. An exemplary method comprises: obtaining at least one log message, wherein the at least one log message comprises a message template and at least one message variable, wherein the message template comprises at least one field corresponding to the at least one message variable; obtaining a compression index that maps a plurality of message templates to a corresponding message signature; identifying a predefined field type of the at least one field; selecting a compression technique to apply to the at least one message variable based on the predefined field type to obtain a compressed message variable; and writing the compressed message variable and a message signature corresponding to the message template of the at least one log message to a log file. The at least one log message can be a historical log message or part of a real-time stream of log messages.