Video coding systems or apparatus utilizing context-based adaptive binary arithmetic coding (CABAC) during encoding and/or decoding, are configured according to the invention with an enhanced binarization of non-zero Delta-QP (dQP). During binarization the value of dQP and the sign are separately encoded using unary coding and then combined into a binary string which also contains the dQP non-zero flag. This invention capitalizes on the statistical symmetry of positive and negative values of dQP and results in saving bits and thus a higher coding efficiency.

Embodiments of this disclosure provide for a data compression method and a related data compression apparatus. In the method, to-be-compressed data and a length limit value for data compression are obtained. When the length of the data obtained by compressing the to-be-compressed data is greater than the length limit value, the to-be-compressed data is segmented based on the length limit value during compression. After the to-be-compressed data is segmented, the to-be-compressed data includes at least two compressed files after compression and a length of each compressed file is less than the length limit value.

The present invention discloses a compensation table compression method, a display manufacturing apparatus, and a memory. The method includes: obtaining a reference frame compensation table and a current frame compensation table; dividing the reference frame compensation table and the current frame compensation table into a plurality of coding blocks, wherein each coding block is separately processed by using multiple prediction modes to obtain a residual coding block in the corresponding prediction mode; and compressing the residual coding block. By using the above method, the invention can save resources, reduce costs, and improve work efficiency.

Techniques and systems are provided for compressing data in a neural network. For example, output data can be obtained from a node of the neural network. Re-arranged output data having a re-arranged scanning pattern can be generated. The re-arranged output data can be generated by re-arranging the output data into the re-arranged scanning pattern. One or more residual values can be determined for the re-arranged output data by applying a prediction mode to the re-arranged output data. The one or more residual values can then be compressed using a coding mode.

Verification of discriminative models includes receiving an input; receiving a prediction from a discriminative model for the input; encoding, using an encoder, a latent variable based on the input; decoding, using a decoder, a reconstructed input based on the prediction and the latent variable; and determining, using an anomaly detection module, whether the prediction is reliable based on the input, the reconstructed input, and the latent variable. The encoder and the decoder are jointly trained to maximize an evidence lower bound of the encoder and the decoder. In some embodiments, the encoder and the decoder are further trained using a disentanglement constraint between the prediction and the latent variable. In some embodiments, the encoder and the decoder are further trained without using inputs that are out of a distribution of inputs used to train the discriminative model or that are adversarial to the discriminative model.

The entropy coding of a current part of a predetermined entropy slice is based on, not only, the respective probability estimations of the predetermined entropy slice as adapted using the previously coded part of the predetermined entropy slice, but also probability estimations as used in the entropy coding of a spatially neighboring, in entropy slice order preceding entropy slice at a neighboring part thereof. Thereby, the probability estimations used in entropy coding are adapted to the actual symbol statistics more closely, thereby lowering the coding efficiency decrease normally caused by lower-delay concepts. Temporal interrelationships are exploited additionally or alternatively.

A radio frequency (RF) unit, a digital unit, and methods of transmitting and receiving data in a wireless communication system are provided. The digital unit may include: a transceiver configured to receive compressed data from an RF unit, a processor configured to divide a frequency domain and a time domain into a plurality of blocks, set a compression parameter to be applied to each of the plurality of blocks, and expand the received data in units of the blocks based on the set compression parameter, and a memory storing the compression parameter.

Computer-implemented methods, systems, and devices to perform lossless compression of floating point format time-series data are disclosed. A first data value may be obtained in floating point format representative of an initial time-series parameter. For example, an output checkpoint of a computer simulation of a real-world event such as weather prediction or nuclear reaction simulation. A first predicted value may be determined representing the parameter at a first checkpoint time. A second data value may be obtained from the simulation. A prediction error may be calculated. Another predicted value may be generated for a next point in time and may be adjusted by the previously determined prediction error (e.g., to increase accuracy of the subsequent prediction). When a third data value is obtained, the adjusted prediction value may be used to generate a difference (e.g., XOR) for storing in a compressed data store to represent the third data value.

Methods, devices and systems enhance compression and decompression of data blocks of data values by selecting the best suited compression method and device among two or a plurality of compression methods and devices, which are combined together and which said compression methods and devices compress effectively data values of particular data types; said best suited compression method and device is selected using as main selection criterion the dominating data type in a data block by predicting the data types within said data block.

The present technology relates to a data processing apparatus, data processing method, and a program which improve a compression ratio. Provided are a first compression part compressing data using compressed sensing and a second compression part compressing observation coefficients coming from the first compression part using a method different from the method used in the first compression part. The first compression part performs random sampling using a sampling matrix optimized for compression by the second compression part. The sampling matrix is designed to minimize the differential value between the observation coefficients. The present technology can be applied to recording/reproducing apparatuses that capture, compress, record, and reproduce image data.