Open Access   Article Go Back

A Survey on Despeckling Of Synthetic Aperture Radar Images

V.B.Pravalika 1 , S. Nageswararoa2 , B. Seetharamulu3

Section:Survey Paper, Product Type: Journal Paper
Volume-7 , Issue-4 , Page no. 608-612, Apr-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i4.608612

Online published on Apr 30, 2019

Copyright © V.B.Pravalika, S. Nageswararoa, B. Seetharamulu . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

View this paper at   Google Scholar | DPI Digital Library

How to Cite this Paper

  • IEEE Citation
  • MLA Citation
  • APA Citation
  • BibTex Citation
  • RIS Citation

IEEE Style Citation: V.B.Pravalika, S. Nageswararoa, B. Seetharamulu, “A Survey on Despeckling Of Synthetic Aperture Radar Images,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.4, pp.608-612, 2019.

MLA Style Citation: V.B.Pravalika, S. Nageswararoa, B. Seetharamulu "A Survey on Despeckling Of Synthetic Aperture Radar Images." International Journal of Computer Sciences and Engineering 7.4 (2019): 608-612.

APA Style Citation: V.B.Pravalika, S. Nageswararoa, B. Seetharamulu, (2019). A Survey on Despeckling Of Synthetic Aperture Radar Images. International Journal of Computer Sciences and Engineering, 7(4), 608-612.

BibTex Style Citation:
@article{Nageswararoa_2019,
author = {V.B.Pravalika, S. Nageswararoa, B. Seetharamulu},
title = {A Survey on Despeckling Of Synthetic Aperture Radar Images},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {4 2019},
volume = {7},
Issue = {4},
month = {4},
year = {2019},
issn = {2347-2693},
pages = {608-612},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=4084},
doi = {https://doi.org/10.26438/ijcse/v7i4.608612}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i4.608612}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=4084
TI - A Survey on Despeckling Of Synthetic Aperture Radar Images
T2 - International Journal of Computer Sciences and Engineering
AU - V.B.Pravalika, S. Nageswararoa, B. Seetharamulu
PY - 2019
DA - 2019/04/30
PB - IJCSE, Indore, INDIA
SP - 608-612
IS - 4
VL - 7
SN - 2347-2693
ER -

VIEWS PDF XML
283 176 downloads 155 downloads
  
  
           

Abstract

Synthetic Aperture Radar (SAR) is a technology used for producing satellite images with high resolution. Since few decades SAR imagery has been the most famous and prominent thing in the context of earth’s observation because of its capability of penetrating through the soils and clouds. Also, SAR imagery has a good ability to operate at any condition type of weather during days and nights. In Remote Sensing technology it is playing a vital role because of this capability and ability. But the presence of undesirable data influences the actual details of the SAR image. This undesirable data is called as noise. This specific noise is also called as “Speckle”. The SAR images are corrupted by the presence of this strong noise. Over few years many techniques have been used to remove the noise from SAR imagery. This process of removing the speckles or noise from SAR imagery is called as Despeckling. In this paper, different methods which are used for removing the noise are discussed.

Key-Words / Index Term

Synthetic Aperture Radar, Speckle, Despeckling

References

[1] Yaser Arianpour, Hamidreza Aminavar, James A. ritcey, “Gradient based SAR image despeckling and super resolution usimg Zernike moments and boostrapping”, in the proceedings of the 2017 IEEE Radar Conference, USA, 2017.
[2] Gao Chen, Gang Li, Yu Liu, Xiao-Ping Zhang, Li Zhang, “SAR image despeckling by combination of fractional-order total variation and non-local low rank regularization”, in the proceedings of the 2017 IEEE International Conference on Image Processing, Beijing, China, 2017.
[3] G. Chierchia, D.Cozzolino, G.Poggi, L.Verdoliva, “Sar image despeckling through convolutional neural networks”, IEEE Signal Processing Letters, Vol.24, Issue.12, pp.1763-1767, 2017.
[4] Qingjun Zhang, Tengfei Li, Yu Zhu, ZhengLv, “Sar image despeckling based on a novel total variation regularization model and gf-3 data”, in the proceedings of the 2018 IEEE International Geoscience and Remote Sensing Symposium, Beijing, China, 2018.
[5] Jie Geng, Jianchao Fan, Xiaorui Ma, Hongyu Wang, Ke Cao, “An iterative low-rank representation for sar image Despeckling”, in the proceedings of the 2016 IEEE International Geoscience and Remote Sensing Symposium, Beijing, China, 2016.
[6] FengGu, Hong Zhang, Chao Wang, Bo Zhang, “Residual encoder-decoder network introduced for multisource sar image Despeckling”, IEEE publisher, Beijing, China 2017.
[7] Weiping Ni and Xinbo Gao, “Despeckling of SAR Image Using Generalized Guided Filter With Bayesian Nonlocal Means”, IEEE Transactions On Geoscience And Remote Sensing, Vol.54, Issue.1, 2016.
[8] Zhenchuan Pang, Guanghi Zhao, Guangng Shi, Fangfang Shen, “SAR Image Despeckling with Adaptive Sparse Representation”, in the proceedings of the 2015 2nd IEEE International Conference on Spatial Data Mining and Geographical Knowledge Services, Fuzhou, China, 2015.
[9] Yao Zhao, Jianguo Liu, Bingchen Zhang, Wen Hong, Yirong Wu, “An adaptive total variation regularization method for sar image Despeckling”, in the proceedings of the 2013 IEEE International Geoscience and Remote Sensing Symposium, Melbourne, VIC, Australia, 2014.
[10] Aiyeola Sikiru Yommy, Rongke Liu, Spencer Ojogba Onuh and Ani Cosmas Ikechukwu, “SAR Image Despeckling and Compression Using K-Nearest Neighbour Based Lee Filter and Wavelet”, in the proceedings of 8th International Congress on Image and Signal Processing, Shenyang, China, 2016.
[11] NageswaraRao Sirisala and C.Shoba Bindu, “A Novel QoS Trust Computation in MANETs Using Fuzzy Petri Nets, International Journal of Intelligent Engineering and Systems”, Vol.10, No.2, (2017), pp 116-125
[12] NageswaraRao Sirisala and C.Shoba Bindu, “Uncertain Rule Based Fuzzy Logic QoS Trust Model in MANETs, International Conference on Advanced Computing and Communications –ADCOM”, (IITM PhD forum), (2015), pp.55-60.1