Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/163501
Title: High-Performance Compression of Multibeam Echosounders Water Column Data
Author: Portell i de Mora, Jordi
Amblàs i Novellas, David
Mitchell, Garrett
Morales, Matias
Villafranca, Alberto G.
Iudica, Ricardo
Lastras Membrive, Galderic
Keywords: Fons marins
Geologia submarina
Ocean bottom
Submarine geology
Issue Date: 28-May-2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Abstract: Over the last few decades, multibeam echosounders (MBES) have become the dominant technique to efficiently and accurately map the seafloor. They now allow to collect water column acoustic images along with the bathymetry, which is providing a wealth of new possibilities in oceans exploration. However, water column imagery generates vast amounts of data that poses obvious logistic, economic, and technical challenges. Surprisingly, very few studies have addressed this problem by providing efficient lossless or lossy data compression solutions. Currently, the available options are only lossless, providing low compression ratios at low speeds. In this paper, we adapt a data compression algorithm, the Fully Adaptive Prediction Error Coder (FAPEC), which was created to offer outstanding performance under the strong requirements of space data transmission. We have added to this entropy coder a specific pre-processing stage tailored to theKongsbergMaritime water column file formats. Here, we test it on data acquired with Kongsberg MBES models EM302, EM710, andEM2040.With this bespoke pre-processing, FAPEC provides good lossless compression ratios at high speeds, whereas lossy ratios reach water column file sizes even smaller than bathymetry raw files still with good image quality. We show the advantages over other lossless compression solutions, both in terms of compression ratios and speed.We illustrate the quality of water column images after lossy FAPEC compression, as well as its resilience to datagram errors and its potential for automatic detection of water column targets. We also show the successful integration in ARM microprocessors (like those used by smartphones and also by autonomous underwater vehicles), which provides a real-time solution for MBES water column data compression.
Note: Versió postprint del document publicat a: https://doi.org/10.1109/JSTARS.2019.2915844
It is part of: IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2019, vol. 12, num. 6, p. 1771-1783
URI: http://hdl.handle.net/2445/163501
Related resource: https://doi.org/10.1109/JSTARS.2019.2915844
ISSN: 1939-1404
Appears in Collections:Articles publicats en revistes (Dinàmica de la Terra i l'Oceà)

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