NDLI: Fast and efficient algorithm for real time lossless compression of LiDAR rasterized data Based on improving energy compaction

Content Provider	IEEE Xplore Digital Library
Author	Ghamisi, Pedram Sepehrband, Farshid Mohammadzadeh, Ali Mortazavi, Mohammad Choupan, Jeiran
Copyright Year	2011
Description	Author affiliation: School of Science and Engineering, K. N. Toosi University of Technology, Tehran, Iran (Ghamisi, Pedram; Mohammadzadeh, Ali) \|\| School of Science and Engineering, Sharif University of Technology, International Campus, Kish Island, Iran (Sepehrband, Farshid; Mortazavi, Mohammad; Choupan, Jeiran)
Abstract	LiDAR rasterized data contain a large amount of information such as elevation of earth surface and is regarding to a lot of fields of Remote Sensing such as flood monitoring, urban management, agriculture and so on. In the field of flood monitoring application, real time processing and fast transmission system for LiDAR rasterized data are required. Compression helps transmission system to work faster. Also, a low complex algorithm makes real time process quick. However, due to importance of LiDAR information, lossless compression is preferred. There are few powerful compression methods available such as JPEG2000, but they are complex. On the other hand, low complex methods such as lossless JPEG are not efficient in compression ratio. In this paper, simplicity of prediction models for image transformation is used to introduce a low complex and efficient lossless compression method for LiDAR rasterized data based on improving energy compaction ability of prediction models. Further, proposed method is applied on few LiDAR test cases and results indicate that the lossless compression method caused high speed transmission system because of good compression ratio and simplicity and suggest to use in real time processing of LiDAR technology.
Starting Page	297
Ending Page	300
File Size	1956037
Page Count	4
File Format	PDF
ISBN	9781424486588
e-ISBN	9781424486571
DOI	10.1109/JURSE.2011.5764778
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-04-11
Publisher Place	Germany
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Real time systems Image coding Laser radar LiDAR Technology Transform coding Lossless Compression Image Transformation Entropy Compaction Remote Sensing (RS) Remote sensing
Content Type	Text
Resource Type	Article

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