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

A fast ELM-based machine compression scheme for underwater image transmission on a low-bandwidth... This paper aims to propose a fast machine compression scheme, which can solve the problem of low-bandwidth transmission for underwater images.Design/methodology/approachThis 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.FindingsExperiment 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/valueThis 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Sensor Review Emerald Publishing

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

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References (28)

Publisher
Emerald Publishing
Copyright
© Emerald Publishing Limited
ISSN
0260-2288
DOI
10.1108/sr-08-2018-0204
Publisher site
See Article on Publisher Site

Abstract

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

Journal

Sensor ReviewEmerald Publishing

Published: Jul 26, 2019

Keywords: Extreme learning machine; Image compression; Principal components analysis

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