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Volume 42 Issue 6
Jun.  2020
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Lianyin JIA, Mingxian CHEN, Mengjuan LI, Jinguo YOU, Jiaman DING. State View Based Efficient Hilbert Encoding and Decoding Algorithms[J]. Journal of Electronics & Information Technology, 2020, 42(6): 1494-1501. doi: 10.11999/JEIT190501
Citation: Lianyin JIA, Mingxian CHEN, Mengjuan LI, Jinguo YOU, Jiaman DING. State View Based Efficient Hilbert Encoding and Decoding Algorithms[J]. Journal of Electronics & Information Technology, 2020, 42(6): 1494-1501. doi: 10.11999/JEIT190501

State View Based Efficient Hilbert Encoding and Decoding Algorithms

doi: 10.11999/JEIT190501
Funds:  The National Natural Science Foundation of China (61562054), Fund of China Scholarship Council (201908530036)
  • Received Date: 2019-07-05
  • Rev Recd Date: 2020-02-03
  • Available Online: 2020-02-27
  • Publish Date: 2020-06-22
  • Hilbert curve is an important method for high-dimensional reduction to one-dimensional. It has good characteristics of spatial aggregation and spatial continuity and is widely used in geographic information system, spatial databases and information retrieval. Existing Hilbert encoding or decoding algorithms do not consider the differences between input data, thus treating them equally. To this end, an efficient Hilbert coding algorithm Front-Zero-Free Hilbert Encoding(FZF-HE) and an efficient decoding algorithm Front-Zero-Free Hilbert Decoding(FZF-HD) are proposed. FZF-HE and FZF-HD can quickly identify the 0 s of the front part of input data before iterative calculation by combining efficient state views and first bit-1 detection algorithm, thus reducing the number of iterations and the complexity of the algorithm, and improving the encoding and decoding efficiency. The experimental results show that efficiencies of these two algorithms are slightly higher than existing algorithms for uniform distributed data, and are much higher than existing algorithms for skew distributed data.

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