Title :
An Lidar data compression method based on improved LZW and Huffman algorithm
Author :
Zhang, Yikun ; Li, Xiao ; Hua, Dengxin ; Chen, Hao ; Jin, Haiyan
Author_Institution :
Xi´´an Univ. of Technol., Xi´´an, China
Abstract :
Lidar raw echo data has characteristics such as huge data quantity, strong discreteness and unpredictability. According to the construction of Lidar monitoring network of atmospheric environment, the existing network can not provide enough bandwidth to transmit Lidar data in real time. In this paper, we propose a novel hybrid lossless compression algorithm to reduce the transmission amount, namely the probability statistics lossless compression algorithm base on the improved LZW(Lempel-Ziv-Welch), which combines Huffman coding. With experiment on the raw two-value atmospheric data, we verify the effectiveness of our approach that the compression ratio is close to 9.5:1 and the coding efficiency is up to 98%.
Keywords :
Huffman codes; optical radar; probability; statistics; Huffman algorithm; Huffman coding; LZW; Lempel-Ziv-Welch; data compression method; hybrid lossless compression algorithm; lidar; probability statistics lossless compression algorithm; Algorithm design and analysis; Compression algorithms; Data compression; Dictionaries; Image coding; Laser radar; Monitoring; Huffman; Hybrid lossless compression method; LZW; Lidar data;
Conference_Titel :
Electronics and Information Engineering (ICEIE), 2010 International Conference On
Conference_Location :
Kyoto
Print_ISBN :
978-1-4244-7679-4
Electronic_ISBN :
978-1-4244-7681-7
DOI :
10.1109/ICEIE.2010.5559775