Image Speckle Denoising for Securing Internet of Smart Sensors

How to improve utility performance when securing sensitive data is an important research problem in Internet of smart sensors. In this paper, we study secured image speckle denoising for networked synthetic aperture radar (SAR). Speckle noise of SAR affects image quality and has a great influence on...

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Autores principales:	Wei Ma, Zhihui Xin, Licun Sun, Jun Zhang
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi-Wiley 2021
Materias:	Technology (General) T1-995 Science (General) Q1-390
Acceso en línea:	https://doaj.org/article/f26760b53a494001895f9f0a8fcc51e0
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id	oai:doaj.org-article:f26760b53a494001895f9f0a8fcc51e0
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spelling	oai:doaj.org-article:f26760b53a494001895f9f0a8fcc51e02021-11-29T00:55:48ZImage Speckle Denoising for Securing Internet of Smart Sensors1939-012210.1155/2021/2610887https://doaj.org/article/f26760b53a494001895f9f0a8fcc51e02021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/2610887https://doaj.org/toc/1939-0122How to improve utility performance when securing sensitive data is an important research problem in Internet of smart sensors. In this paper, we study secured image speckle denoising for networked synthetic aperture radar (SAR). Speckle noise of SAR affects image quality and has a great influence on target detection and recognition. MSTAR dataset is often used in image target recognition. In this paper, a subregion-based method is proposed in order to improve the accuracy of target recognition and better retain target information while filtering and denoising the image. The new method applies advanced encryption techniques to protect sensitive data against malicious attack. Firstly, the image is divided into marked areas and unmarked areas through edge extraction and hole filling. Secondly, we use different size windows and filtering methods to filter the image in different areas. The experimental results show that the proposed algorithm has obvious advantages over MR-NLM, SSIM-NLM, Frost, and BM3D filtering in terms of equivalent view number and preserving edge and structure.Wei MaZhihui XinLicun SunJun ZhangHindawi-WileyarticleTechnology (General)T1-995Science (General)Q1-390ENSecurity and Communication Networks, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Technology (General) T1-995 Science (General) Q1-390
spellingShingle	Technology (General) T1-995 Science (General) Q1-390 Wei Ma Zhihui Xin Licun Sun Jun Zhang Image Speckle Denoising for Securing Internet of Smart Sensors
description	How to improve utility performance when securing sensitive data is an important research problem in Internet of smart sensors. In this paper, we study secured image speckle denoising for networked synthetic aperture radar (SAR). Speckle noise of SAR affects image quality and has a great influence on target detection and recognition. MSTAR dataset is often used in image target recognition. In this paper, a subregion-based method is proposed in order to improve the accuracy of target recognition and better retain target information while filtering and denoising the image. The new method applies advanced encryption techniques to protect sensitive data against malicious attack. Firstly, the image is divided into marked areas and unmarked areas through edge extraction and hole filling. Secondly, we use different size windows and filtering methods to filter the image in different areas. The experimental results show that the proposed algorithm has obvious advantages over MR-NLM, SSIM-NLM, Frost, and BM3D filtering in terms of equivalent view number and preserving edge and structure.
format	article
author	Wei Ma Zhihui Xin Licun Sun Jun Zhang
author_facet	Wei Ma Zhihui Xin Licun Sun Jun Zhang
author_sort	Wei Ma
title	Image Speckle Denoising for Securing Internet of Smart Sensors
title_short	Image Speckle Denoising for Securing Internet of Smart Sensors
title_full	Image Speckle Denoising for Securing Internet of Smart Sensors
title_fullStr	Image Speckle Denoising for Securing Internet of Smart Sensors
title_full_unstemmed	Image Speckle Denoising for Securing Internet of Smart Sensors
title_sort	image speckle denoising for securing internet of smart sensors
publisher	Hindawi-Wiley
publishDate	2021
url	https://doaj.org/article/f26760b53a494001895f9f0a8fcc51e0
work_keys_str_mv	AT weima imagespeckledenoisingforsecuringinternetofsmartsensors AT zhihuixin imagespeckledenoisingforsecuringinternetofsmartsensors AT licunsun imagespeckledenoisingforsecuringinternetofsmartsensors AT junzhang imagespeckledenoisingforsecuringinternetofsmartsensors
_version_	1718407807643942912

Image Speckle Denoising for Securing Internet of Smart Sensors

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