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Computer-Aided Civil and Infrastructure Engineering
Article . 2017 . Peer-reviewed
License: CC BY NC ND
Data sources: Crossref
DBLP
Article . 2017
Data sources: DBLP
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The Fast Prefix Coding Algorithm (FPCA) for 3D Pavement Surface Data Compression

Authors: Allen Zhang 0001; Kelvin C. P. Wang;

The Fast Prefix Coding Algorithm (FPCA) for 3D Pavement Surface Data Compression

Abstract

The enormous data inflow during three-dimensional 3D pavement surface data collection requires an efficient compression system for 3D data. However, with respect to the phase of lossless encoding, the commonly used Huffman Coding is inefficient in terms of speed and memory usage for encoding 3D pavement surfaces. The Fast Prefix Coding Algorithm FPCA is proposed in the article as an effective substitute of Huffman Coding at the stage of lossless encoding. It is demonstrated in the article that the FPCA is much faster and more memory efficient than Huffman Coding, while outperforming Shannon-Fano Coding in terms of both redundancy and time efficiency. The FPCA-based coding approach is a modification of the baseline JPEG algorithm to support 3D pavement data whose dynamic range is more than 12 bits. The presented modifications include algorithms for Quantization, Run-Length Encoding and Entropy Coding without limiting data depth in terms of dynamic range. Compared with the baseline JPEG approach, the proposed coding system is able to restrict the data loss more successfully and can achieve a significantly higher level of time efficiency and compression ratio over than 30:1 for most of the evaluated 3D images. With parallel computing techniques, encoding full-lane width pavement in 3D and at 1 mm resolution with an up-to-date desktop computer can be conducted at 150 MPH or even higher speed.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
17
Top 10%
Top 10%
Top 10%
hybrid