A Survey on Techniques Used for De-Speckling of SAR Images

Author:

Kumar Bibek1ORCID,Ranjan Ranjeet Kumar1,Husain Arshad1

Affiliation:

1. DIT University, India

Abstract

Because of the capacity to work at any climate circumstance and infiltration ability through the clouds and soil, SAR (Synthetic Aperture Radar) imagery has been very demanding.SAR imagery system captures images from any satellite or moving object such as aircraft etc. As per the height of a RADAR system increases the resolution of SAR images is also increased. Due to high-resolution images and multiplicative noise known as speckle, it is not easy to analyze these images. So, it has become very important to remove speckle from these images.There are great numbers of de-speckling techniques have been proposed in past. It is very difficult to identify a suitable technique for a de-speckling task. In this article, authors have proposed a literature survey of some techniques.Authors compared best techniques based on their merits and the different parameters used so far for the observation of SAR images. In recent years, the popularity of deep learning has grown tremendously. For de-speckling of SAR images, various improved CNNs and deep learning based approaches have been proposed.

Publisher

IGI Global

Subject

Management, Monitoring, Policy and Law,Development,Ecology,Environmental Engineering

Reference34 articles.

1. Speckle Reducing Anisotropic Diffusion for Echocardiography

2. Ali, S. M., Javed, M. Y., & Khattak, N. S. (2007). Wavelet-Based Despeckling of Synthetic Aperture Radar Images Using Adaptive and Mean Filters. Engineering and Technology International Journal of Computer, Electrical, Automation, Control and Information Engineering, 1(7).

3. A Tutorial on Speckle Reduction in Synthetic Aperture Radar Images

4. Wavelet-based spatially adaptive method for despeckling SAR images

5. SAR image change detection based on deep denoising and CNN

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Ship Detection from Despeckled Satellite Images using Deep Learning;2022 IEEE International Conference on Data Science and Information System (ICDSIS);2022-07-29

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3