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Denoising ISTA-Net: learning based compressive sensing with reinforced non-linearity for side scan sonar image denoising

Authors
Lee, BokyeungKu, BonwhaKim, Wan-JinKim, SeongilKo, Hanseok
Issue Date
2020
Publisher
ACOUSTICAL SOC KOREA
Keywords
Side scan sonar; Image denoising; Compressive sensing; Learning based compressive sensing
Citation
JOURNAL OF THE ACOUSTICAL SOCIETY OF KOREA, v.39, no.4, pp.246 - 254
Indexed
SCOPUS
KCI
Journal Title
JOURNAL OF THE ACOUSTICAL SOCIETY OF KOREA
Volume
39
Number
4
Start Page
246
End Page
254
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/59025
DOI
10.7776/ASK.2020.39.4.246
ISSN
1225-4428
Abstract
In this paper, we propose a learning based compressive sensing algorithm for the purpose of side scan sonar image denoising. The proposed method is based on Iterative Shrinkage and Thresholding Algorithm (ISTA) framework and incorporates a powerful strategy that reinforces the non-linearity of deep learning network for improved performance. The proposed method consists of three essential modules. The first module consists of a non-linear transform for input and initialization while the second module contains the ISTA block that maps the input features to sparse space and performs inverse transform. The third module is to transform from non-linear feature space to pixel space. Superiority in noise removal and memory efficiency of the proposed method is verified through various experiments.
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