Decomposing a value range of the respective syntax elements into a sequence of n partitions with coding the components of z laying within the respective partitions separately with at least one by VLC coding and with at least one by PIPE or entropy coding is used to greatly increase the compression efficiency at a moderate coding overhead since the coding scheme used may be better adapted to the syntax element statistics. Accordingly, syntax elements are decomposed into a respective number n of source symbols s.sub.i with i=1 . . . n, the respective number n of source symbols depending on as to which of a sequence of n partitions into which a value range of the respective syntax elements is sub-divided, a value z of the respective syntax elements falls into, so that a sum of values of the respective number of source symbols s.sub.i yields z, and, if n>1, for all i=1 . . . n1, the value of s.sub.i corresponds to a range of the i.sup.th partition.

A network node includes a processor programmed to parse at least a portion of an input block having a plurality of segments, determine whether at least one of the plurality of segments matches a segment stored in a history buffer, and predict a compressibility of the input block based at least in part on whether at least one of the plurality of segments matches a segment stored in the history buffer.

Methods and apparatus are provided for improved entropy encoding and decoding. An apparatus includes a video encoder (200) for encoding at least a block in a picture by transforming a residue of the block to obtain transform coefficients, quantizing the transform coefficients to obtain quantized transform coefficients, and entropy coding the quantized transform coefficients. The quantized transform coefficients are encoded using a flag to indicate that a current one of the quantized transform coefficients being processed is a last non-zero coefficient for the block having a value greater than or equal to a specified value.

An image coding method using arithmetic coding. The method includes: performing arithmetic coding on a first flag that indicates whether or not an absolute value of a target coefficient in a target coefficient block is greater than 1; and performing arithmetic coding on a second flag that indicates whether or not the absolute value is greater than 2. In the arithmetic coding on the first flag and the arithmetic coding on the second flag, it is determined whether or not an immediately-prior coefficient block that has been coded immediately prior to the target coefficient block includes a coefficient having an absolute value greater than a threshold value. Based on a result of the determination, respective contexts to be used in the arithmetic coding on the first and second flags are selected.

Decomposing a value range of the respective syntax elements into a sequence of n partitions with coding the components of z laying within the respective partitions separately with at least one by VLC coding and with at least one by PIPE or entropy coding is used to greatly increase the compression efficiency at a moderate coding overhead since the coding scheme used may be better adapted to the syntax element statistics. Accordingly, syntax elements are decomposed into a respective number n of source symbols s.sub.i with i=1 . . . n, the respective number n of source symbols depending on as to which of a sequence of n partitions into which a value range of the respective syntax elements is sub-divided, a value z of the respective syntax elements falls into, so that a sum of values of the respective number of source symbols s.sub.i yields z, and, if n>1, for all i=1 . . . n1, the value of s.sub.i corresponds to a range of the i.sup.th partition.

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.

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.

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.

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.