|Start Page Number:||173|
|End Page Number:||190|
|Publication Date:||Mar 2017|
|Journal:||Computer-Aided Civil and Infrastructure Engineering|
|Authors:||Wang Kelvin C P, Zhang Allen|
|Keywords:||transportation: road, computers: data-structure, computers: information, storage|
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.