An arithmetic encoder for encoding a plurality of symbols having symbol values is configured to derive an interval size information for an arithmetic encoding of one or more symbol values to be encoded based on a plurality of state variable values representing statistics of a plurality of previously encoded symbol values with different adaptation time constants. The arithmetic encoder is configured to map a first state variable value, or a scaled and/or rounded version thereof, using a lookup-table and to map a second state variable value, or a scaled and/or rounded version thereof using the lookup-table, in order to obtain the interval size information describing an interval size for the arithmetic encoding of one or more symbols to be encoded. Further arithmetic encoders, arithmetic decoders, video encoders, video decoder, methods for encoding, methods for decoding and computer programs are also disclosed which are based on the same concept and on other concepts.

A data compression method, comprising: obtaining a plurality of values of a parameter and an occurrence probability of each of the plurality of values (S101) comparing the occurrence probability with a predetermined threshold, wherein values with the occurrence probability less than the predetermined threshold are first set of values, and values with the occurrence probability greater than or equal to the predetermined threshold are second set of values (S102), performing pretreatment on the first set of values (S103), and encoding the second set of values and the pretreated first set of values (S104). By means of the data compression method, the maximum codeword length can be effectively reduced, so as to reduce the requirements of a code table to the storage space.

A data compression method comprises encoding groups of data items by generating, for each group, header data comprising h-bits and a plurality of body portions each comprising b-bits and each body portion corresponding to a data item in the group. The value of h may be fixed for all groups and the value of b is fixed within a group, wherein the header data for a group comprises an indication of b for the body portions of that group. In various examples, b=0 and so there are no body portions. In examples where b is not equal to zero, a body data field is generated for each group by interleaving bits from the body portions corresponding to data items in the group. The resultant encoded data block, comprising the header data and, where present, the body data field can be written to memory.

A system comprises an encoder configured to entropy encode a bitstream comprising both compressible and non-compressible symbols. The encoder parses the bitstream into a compressible symbol sub-stream and a non-compressible sub-stream. The non-compressible symbol sub-stream bypass an entropy encoding component of the encoder while the compressible symbol sub-stream is entropy encoded. When a quantity of bytes of entropy encoded symbols and bypass symbols is accumulated a chunk of fixed or known size is formed using the accumulated entropy encoded symbol bytes and the bypass bytes without waiting on the full bitstream to be processed by the encoder. In a complementary manner, a decoder reconstructs the bitstream from the packets or chunks.

According to the invention, there are provided sets of contexts specifically adapted to encode special coefficients of a prediction error matrix, on the basis of previously encoded values of level k. Furthermore, the number of values of levels other than 0 is explicitly encoded and numbers of appropriate contexts are selected on the basis of the number of spectral coefficients other than 0.

According to the invention, there are provided sets of contexts specifically adapted to encode special coefficients of a prediction error matrix, on the basis of previously encoded values of level k. Furthermore, the number of values of levels other than 0 is explicitly encoded and numbers of appropriate contexts are selected on the basis of the number of spectral coefficients other than 0.

According to the invention, there are provided sets of contexts specifically adapted to encode special coefficients of a prediction error matrix, on the basis of previously encoded values of level k. Furthermore, the number of values of levels other than 0 is explicitly encoded and numbers of appropriate contexts are selected on the basis of the number of spectral coefficients other than 0.

According to the invention, there are provided sets of contexts specifically adapted to encode special coefficients of a prediction error matrix, on the basis of previously encoded values of level k. Furthermore, the number of values of levels other than 0 is explicitly encoded and numbers of appropriate contexts are selected on the basis of the number of spectral coefficients other than 0.

Method for encoding of quality values of a data structure, whereby said data structure comprises a set of genomic reads, wherein the method comprises the following steps executable by a data processing system: ascertain the quality values of each read covering a certain index locus, determine a codebook identifier identifying a specific codebook from a plurality of codebooks for said certain index locus based on the ascertained quality values of said certain index locus, whereby each code-book provides a mapping from a quality value of said quality value alphabet to a corresponding quantized quality value of a quantized quality value alphabet, quantizing all ascertained quality values at said certain index locus using the specific codebook identified by the codebook identifier at said certain index locus in order to obtain for each quality value at said certain index locus a corresponding quantized quality value, and encode all determined codebook identifiers using a first entropy encoder and encode all quantized quality values using a second entropy encoder or a set of encoders.

A predictive model utilizes a set of coefficients for processing received input data. To reduce memory usage storing the coefficients, a compression circuit compresses the set of coefficients prior to storage by generating a cumulative count distribution of the coefficient values, and identifying a distribution function approximating the cumulative count distribution. Function parameters for the determined function are stored in a memory and used by a decompression circuit to apply the function the compressed coefficients to determine the decompressed component values. Storing the function parameters may consume less memory in comparison to storing a look-up table for decompression, and may reduce an amount of memory look-ups required during decompression.