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Erschienen in:
2014 | OriginalPaper | Buchkapitel
Microscan Imager Logging Data Compression Using improved Huffman Algorithm
verfasst von : Yanhui Zhang, He Zhang, Jun Shi, Xiaozheng Yin
Erschienen in: Bio-Inspired Computing - Theories and Applications
Verlag: Springer Berlin Heidelberg
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The conflict between ever-increasing volumes of microscan imager logging data and limited cable transmission bandwidth intensifying day by day. In this paper, an improved lossless data compression algorithm is proposed. Specifically, according to the characteristics of the micro resistivity imaging logging data, it is proved that Hex character encoding has better compressibility than decimal character encoding. Then, it analyzed that traditional quaternary Huffman algorithm does not be fully applicable to microscan imager logging data. Lastly, it employed improved quaternary Huffman algorithm for logging data compression so as to enhance the data compression ratio. The experiment comparsions show that ,compared to the convention quaternary algorithm and the improved compressed Huffman encoding, Both elapsed time and compression ratio are a great improvement.