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A fast ELM-based machine compression scheme for underwater image transmission on a low-bandwidth acoustic channel

Shujing Zhang (Hebei Normal University, Shijiazhuang, China)
Manyu Zhang (Hebei Normal University, Shijiazhuang, China)
Yujie Cui (Hebei Normal University, Shijiazhuang, China)
Xingyue Liu (Hebei Normal University, Shijiazhuang, China)
Bo He (Ocean University of China, Qingdao, China)
Jiaxing Chen (Hebei Normal University, Shijiazhuang, China)

Sensor Review

ISSN: 0260-2288

Article publication date: 15 July 2019

Abstract

Purpose

This paper aims to propose a fast machine compression scheme, which can solve the problem of low-bandwidth transmission for underwater images.

Design/methodology/approach

This fast machine compression scheme mainly consists of three stages. Firstly, raw images are fed into the image pre-processing module, which is specially designed for underwater color images. Secondly, a divide-and-conquer (D&C) image compression framework is developed to divide the problem of image compression into a manageable size. And extreme learning machine (ELM) is introduced to substitute for principal component analysis (PCA), which is a traditional transform-based lossy compression algorithm. The execution time of ELM is very short, thus the authors can compress the images at a much faster speed. Finally, underwater color images can be recovered from the compressed images.

Findings

Experiment results show that the proposed scheme can not only compress the images at a much faster speed but also maintain the acceptable perceptual quality of reconstructed images.

Originality/value

This paper proposes a fast machine compression scheme, which combines the traditional PCA compression algorithm with the ELM algorithm. Moreover, a pre-processing module and a D&C image compression framework are specially designed for underwater images.

Keywords

Acknowledgements

This research is sponsored by National Natural Science Foundation of China (Grant No. 61701165, 61771181, 61603121, 61501168), Natural Science Foundation of Hebei Province (Grant No. F2016205182), Natural Science Foundation of Shandong Province (Grant No. ZR201702220373).

Citation

Zhang, S., Zhang, M., Cui, Y., Liu, X., He, B. and Chen, J. (2019), "A fast ELM-based machine compression scheme for underwater image transmission on a low-bandwidth acoustic channel", Sensor Review, Vol. 39 No. 4, pp. 542-553. https://doi.org/10.1108/SR-08-2018-0204

Publisher

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Emerald Publishing Limited

Copyright © 2019, Emerald Publishing Limited