Despeckling and Analysing Land Use Land Cover of Synthetic Aperture Radar Image
V.B. Pravalika1, S. Nageswararao2
1V.B. Pravalika, CSE, Vardhaman College of Engineering, affiliated with Jawaharlal Nehru Technological University, Hyderabad, India.
2NageswararaoSirisala, CSE, Vardhaman College of Engineering, affiliated with Jawaharlal Nehru Technological University, Hyderabad, India.
Manuscript received on 11 August 2019 | Revised Manuscript received on 18 August 2019 | Manuscript published on 30 August 2019 | PP: 2827-2831 | Volume-8 Issue-10, August 2019 | Retrieval Number: J95990881019/2019©BEIESP | DOI: 10.35940/ijitee.J9599.0881019
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© 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: In Image processing, Synthetic Aperture Radar(SAR) images are inherently affected by speckle noise, which visually degrades the appearance of the images and may severely affect the quality of SAR image interpretation tasks like object detection or target detection, instance segmentation and image analysis. Hence SAR image Despeckling becomes a hot research issue. In this paper, the proposed method Total Variation (TV) Denoising is used to address this issue. It is applied to SAR imagery to decrease the noise. It is a filtering method which works efficiently. The process of decreasing the speckle noise is known as Despeckling. When there is noise in the image the actual data is affected. The actual meaning of noise is unwanted signal. Noise is an undesirable by-product in an image that disturbs the original image. On removal of noise, it results in the noise free SAR image. The Land Use Land Cover (LULC) analysis of a SAR image can be accurate when there is no noise in the SAR image. Therefore the main aim of this paper is to analyze the land use and land cover (LULC) in the despeckled high resolution image.
Keywords: SAR Images, Despeckling, Total Variation, Principal Component Analysis
Scope of the Article: Image Security