A system and method for encoding data using a plurality of encoding libraries. Portions of the data are encoded by different encoding libraries, depending on which library provides the greatest compaction for a given portion of the data. This methodology not only provides substantial improvements in data compaction over use of a single data compaction algorithm with the highest average compaction, but provides substantial additional security in that multiple decoding libraries must be used to decode the data. In some embodiments, each portion of data may further be encoded using different sourceblock sizes, providing further security enhancements as decoding requires multiple decoding libraries and knowledge of the sourceblock size used for each portion of the data. In some embodiments, encoding libraries may be randomly or pseudo-randomly rotated to provide additional security.

Encoding an image includes determining respective costs of coding a symbol using available coding types. A first coding type indicates that a value of the symbol is to be decoded using a same number of bits, and a second coding type indicates that the value of the symbol is to be decoded using a range. An optimal coding type of the available coding types is selected, which corresponds to a smallest cost of the respective costs. A first indicator of the optimal coding type and a first symbol value of the symbol using the optimal coding type are encoded in a compressed bitstream. Decoding an image includes decoding, from a header of a compressed bitstream, respective coding types of symbols encoded in the compressed bitstream and decoding, from the compressed bitstream, respective values of the symbols according to the respective coding types decoded from the header.

A method for sharing a hardware decompression engine, including performing a compression type check on a first data stream to determine a compression type of the first data stream, wherein the first data stream is compressed using one selected from a group consisting of a first compression type and a second compression type; wherein, when the first data stream is compressed with the second compression type: receiving the second compression type at a selector; converting the first data stream compressed with the second compression type into a second data stream of the first compression type; inputting the converted second data stream into the selector; and decompressing the converted second data stream using the hardware decompression engine capable of decompressing a data stream compressed using the first compression type. In other aspects, a system for sharing a hardware decompression engine and a computing system are provided.

Embodiments of the present disclosure provide a method, electronic device and a computer program product for processing data. The method comprises determining target data that are used for determining a target compression level for a user. The method also comprises compressing at least part of the target data using a plurality of compression levels of a compression algorithm, respectively, to obtain a plurality of compression ratios and a plurality of compression latencies corresponding to the plurality of compression levels. The method further comprises determining the target compression level for the user for compressing data of the user data based on the plurality of compression ratios and the plurality of compression latencies.

Methods and systems for improving coding decoding efficiency of video by providing a syntax modeler, a buffer, and a decoder. The syntax modeler may associate a first sequence of symbols with syntax elements. The buffer may store tables, each represented by a symbol in the first sequence, and each used to associate a respective symbol in a second sequence of symbols with encoded data. The decoder decodes the data into a bitstream using the second sequence retrieved from a table.

A system configured to generate a set of compression dictionary snapshots. The system can determine a subset of a set of compression dictionary definitions, the subset having a first subset comprising one or more definitions that have changed since a time of a previous snapshot and a second subset having one or more definitions associated with a predetermined portion of the dictionary. The system can further generate and store snapshots based at least in part on the determined subset of one or more definitions and determine a plurality of active snapshots from the set of snapshots such that the set of one or more definitions is included in the plurality of active snapshots.

A system and method for encoding data using a plurality of encoding libraries. Portions of the data are encoded by different encoding libraries, depending on which library provides the greatest compaction for a given portion of the data. This methodology not only provides substantial improvements in data compaction over use of a single data compaction algorithm with the highest average compaction, but provides substantial additional security in that multiple decoding libraries must be used to decode the data. In some embodiments, each portion of data may further be encoded using different sourceblock sizes, providing further security enhancements as decoding requires multiple decoding libraries and knowledge of the sourceblock size used for each portion of the data. In some embodiments, encoding libraries may be randomly or pseudo-randomly rotated to provide additional security.

Methods and systems for encoding and decoding data, such as point cloud data. The methods may include using a coder map to map a range of discrete dependency states to a smaller set of binary coders each having an associated coding probability. The selection of one of the discrete dependency states may be based on a contextual or situational factors, which may include a prediction process, for a particular symbol, such as an occupancy bit. The coder map is updated after each symbol is coded to possibly alter to which binary coder the selected discrete dependency state maps.

A method and a system for decoding MPEG-G encoded data of genomic information, including: receiving MPEG-G encoded data; extracting encoding parameters; selecting an arithmetic decoding type based upon the extracted encoding parameters; selecting a predictor type specifying the method to obtain probabilities of symbols which were used for arithmetically encoding the data, based upon the extracted encoding parameters; selecting arithmetic coding contexts based upon the extracted encoding parameters; and decoding the encoded data using the selected predictor and the selected arithmetic coding contexts.

A system and method for faster communication between blockchain mining nodes and faster block validation. The system uses machine learning on data chunks to generate codebooks which compact the data to be stored, processed, or sent with a smaller data profile than uncompacted data. The system uses a data compaction in an existing blockchain fork or implemented in a new blockchain protocol from which nodes that wish to or need to use the blockchain can do so with a reduced storage requirement. The system uses network data compaction across all nodes to increase the speed of and decrease the size of a blockchain’s data packets. The system uses data compaction firmware to increase the efficiency at which mining rigs can computationally validate new blocks on the blockchain. The system can be implemented using any combination of the three data compaction services to meet the needs of the desired blockchain technology.