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Reseach Article

Sea Ice Detection using Synthetic Aperture Radar Algorithm in Image Processing

by Amanpreet Kaur, Sandeep Singh Kang
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 121 - Number 13
Year of Publication: 2015
Authors: Amanpreet Kaur, Sandeep Singh Kang
10.5120/21597-4699

Amanpreet Kaur, Sandeep Singh Kang . Sea Ice Detection using Synthetic Aperture Radar Algorithm in Image Processing. International Journal of Computer Applications. 121, 13 ( July 2015), 1-5. DOI=10.5120/21597-4699

@article{ 10.5120/21597-4699,
author = { Amanpreet Kaur, Sandeep Singh Kang },
title = { Sea Ice Detection using Synthetic Aperture Radar Algorithm in Image Processing },
journal = { International Journal of Computer Applications },
issue_date = { July 2015 },
volume = { 121 },
number = { 13 },
month = { July },
year = { 2015 },
issn = { 0975-8887 },
pages = { 1-5 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume121/number13/21597-4699/ },
doi = { 10.5120/21597-4699 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:08:17.748852+05:30
%A Amanpreet Kaur
%A Sandeep Singh Kang
%T Sea Ice Detection using Synthetic Aperture Radar Algorithm in Image Processing
%J International Journal of Computer Applications
%@ 0975-8887
%V 121
%N 13
%P 1-5
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

In this paper I describe detection of sea ice using synthetic aperture radar algorithm. Sea ice detection is one of the important appliances of remote sensing technology. Remote sensing is a technique through which information can be acquired without physical contact. It is a safe supervision for ships to understand the climate conditions of oceans and to navigate the formation of ice maps. The main purpose of sea ice monitoring is to generate the maps of sea ice across the ocean according to their geographical locations. So, in this we will work on sea ice analysis using automated algorithms.

References
  1. Anju Bala, "An improved watershed Image Segmentation Technique using MATLAB", 2012
  2. Cavalieri, D. J. , Parkinson, C. L. , Gloersen, P. , Comiso, J. C. , Zwally, H. J. , "Deriving long term time series of sea ice cover from satellite passive microwave multisensor datasets", J. Geophys. Res. , Vol. 104, No. C7, pp. 15803-15814, 1999.
  3. Bernd Scheuchl et. al, "Potential of RADARSAT-2 data for operational sea ice monitoring", CJRS, 2004
  4. Anderson, H. S. , Long, D. G. , "Sea ice mapping method for Seawinds", IEEE Trans. Geosci. Remote Sens. , Vol. 43(3), 2005.
  5. B. Scheuchl, R. Caves, D. Flett, R. Abreu, M. Arkett, and I. Cumming "ENVISAT ASAR AP data for operational sea ice monitoring" In Proc. IEEE,International Geoscience and Remote Sensing Symposium, volume 3, Sept. 2004
  6. Huawu Deng, David A. Clausi, "Unsupervised Segmentation of Synthetic Aperture Radar Sea Ice imagery using a Novel Markov Random Field Model", IEEE 2005.
  7. Ehmann, J. "Structural Texture Similarity Metrics for Image Analysis and Retrieval", IEEE 2013
  8. Gui Gao, Gongtao Shi and Shilin Zhou, "Ship Detection in High-Resolution Dual-Polarization SAR Amplitude Images" IJAP, volume 3 issue 5, pp- 213-2-15, 2013
  9. Kanchan S. Deshmukh, "Texture Image Segmentation using FCM" 012 IACSIT Hong Kong Conferences IPCSIT vol. 25 2012, IACSIT Press, Singapore
  10. Mandeep Kaur, Gagandeep Singh, " A Review on Sea Ice Analysis", IJSR, 2012.
  11. Marta, Antonio, " Models For Synthetic Aperture Radar Texture Analysis" IEEE 2009
  12. Pham, Tuan D. "Image texture analysis using geostatistical information entropy" IEEE 2012
  13. Peter Yu, A. K Qin, David A. Clausi, "Feature Extraction of dual-pol SAR imagery for sea ice image segmentation ", CASI 2012
  14. Qiyao Yu and David A. Clausi, "SAR Sea Ice Image Analysis Based on Iterative Region Growing Using Semantics ", IEEE 2007
  15. Salem Saleh Al-amri, N. V. Kalyankar and Khamitkar S. D, "Image Segmentation by Using threshold techniques", 2010
  16. Toluope Bamidele Ijitona, Jinchang Ren, Phil Byongjun Hwang, "SAR Sea Ice Image Segmentation Using Watershed with Intensity Based Region Merging" IEEE 2014.
  17. Waller, Ben M. , Mark S. Nixon, and J. N. Carter. "Analysing Micro-and Macro-Structures in Textures. " In Signal Image Technology and Internet Based Systems (SITIS), 2012 Eighth International Conference on, pp. 246-253. IEEE 2012.
  18. Yuliya Tarabalka et. al "Shape-Constrained Segmentation Approach For Arctic Multiyear Sea Ice Floe Analysis", IEEE 2012
  19. Zujovic, Jana, Thrasyvoulos N. Pappas, and David L. Neuhoff. "Structural similarity metrics for texture analysis and retrieval. " In Image Processing (ICIP), 2009 16th IEEE International Conference on, pp. 2225-2228. IEEE 2009.
  20. Mapping of ice, Image. Available online: http://vip. uwaterloo. ca/files/research_images/fig2. PNG
Index Terms

Computer Science
Information Sciences

Keywords

Radar SAR RADARSAT 1 RADARSAT 2 MIRGS