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Content-aware lossless compression and decompression of floating point data

机译:内容感知浮点数据​​的无损压缩和解压缩

摘要

Lossless content-aware compression and decompression techniques are provided for floating point data, such as seismic data. A minimum-length compression technique exploits an association between an exponent and a length of the significand, which corresponds to the position of the least significant bit of the significand. A reduced number of bits from the significand can then be stored. A prediction method is also optionally previously applied, so that residual values with shorter lengths are compressed instead of the original values. An alignment compression technique exploits repetition patterns in the floating point numbers when they are aligned to the same exponent. Floating point numbers are then split into integral and fractional parts. The fractional part is separately encoded using a dictionary-based compression method, while the integral part is compressed using a delta-encoding method. A prediction method is also optionally previously applied to the integral part, thereby increasing the compression ratio.
机译:为浮点数据(例如地震数据)提供了无损内容感知压缩和解压缩技术。最小长度压缩技术利用了指数和有效位长度之间的关联,该关联与有效位最低有效位的位置相对应。然后可以存储从有效位数开始减少的位数。还可选地预先应用预测方法,以便压缩具有较短长度的残差值而不是原始值。对齐压缩技术在将浮点数与相同指数对齐时会利用它们的重复模式。然后将浮点数分为整数部分和小数部分。使用基于字典的压缩方法分别编码小数部分,而使用增量编码方法压缩整数部分。还可选地将预测方法预先应用于整体部分,从而增加压缩率。

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