Analysis of SAR Images using New Image Classification Methods
B. Malakonda Reddy1, Md. Zia Ur Rahman2
1B. Malakonda Reddy, Department of Electronics and Communication Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur-522502, Andhra Pradesh, India.
2Md Zia Ur Rahman, Department of Electronics and Communication Engineering, Koneru Lakshmaiah Education Foundation, Vaddeswaram, Guntur-522502, Andhra Pradesh, India.
Manuscript received on 02 June 2019 | Revised Manuscript received on 10 June 2019 | Manuscript published on 30 June 2019 | PP: 760-764 | Volume-8 Issue-8, June 2019 | Retrieval Number: F3389048619/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Oil spills are carrying out by the marine echo system and these are originated from scientific and political concern since they are seriously affecting the coastal echo system and fragile marine. Oil spills can be detected from the satellite images with more potential by covering the larger areas. While getting satellite images they cover very limited area and require large aperture antennas. But with small aperture and large captured areas Synthetic Aperture Radar (SAR) descriptions are extensively worn in favor of oil spill discovery. In SAR image the oil spill regions can be detected with oil film backscattering. In this process dark patches are formed which are affecting the detection correctness of oil spills. In this occupation oil drop regions are detecting using dual threshold segmentation. In dual threshold segmentation image is partitioned based on histogram analysis. The proposed method illustrates the helpfulness of technique in noticing plus classifying the oil spills.
Keyword: Synthetic-Aperture-Radar(S/A/R), Oil spills, Thresholding, Segmentation.
Scope of the Article: Analysis of Algorithms and Computational Complexity.