Noise Removal Using Thresholding and Segmentation for Random Noise Sentinel-1 Data

Haris Suka Dyatmika and Katmoko Ari Sambodo and Marendra Eko Budiono and Hendayani (2017) Noise Removal Using Thresholding and Segmentation for Random Noise Sentinel-1 Data. In: The 3rd International Symposium on LAPAN-IPB Satellite (LISAT): For Food Security and Environmental Monitoring 2016, 25-26th October 2016, IPB International Convention Center, Bogor, Indonesia.

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Abstract

Sentinel-1 constellation will cover the entire world’s land area continuously. Although Sentinel-1 data show consistency and stability, several noise have been observed in the data i.e. random noise on the right and left of the scene. The noise exists on the right and left of the scene of the SAR data that should be no data value. The noise is quite disturbing and interferes the data especially on mosaic product of some scene data sets. The mosaic product have a seam line that separate a scene and the neighbor that should be disappear after the mosaic process. This paper shows study on how to remove the random noise without losing the information contained. Some Sentinel-1 Level-1 GRD (Ground Range Detected) data in Kalimantan area were used in this study. Principally, the methods used for the noise removal were thresholding and segmentation. If the noise removal process using thresholding only, many noise still exist in the data. Region on the right and left of the scene filtered by a certain value of intensity and segmentation area. Generally, improvement of the data was evaluated both after each scene noise removal process and mosaic product. The noise in each scene Sentinel-1 data disappear and the mosaic product look seamless after applying the noise removal.

Item Type: Conference or Workshop Item (Paper)
Additional Information: IOP Conference Series: Earth and Environmental Science 54 (2017)
Uncontrolled Keywords: Satelit, Sentinel-1, GRD (Ground Range Detected), Kalimantan
Subjects: Teknologi Penginderaan Jauh > Penelitian, Pengkajian, dan Pengembangan > Teknologi dan Data Penginderaan Jauh > Perolehan Data > Satelit
Divisions: Deputi Penginderaan Jauh > Pusat Teknologi dan Data Penginderaan Jauh
Depositing User: Dinar Indrasasi
Date Deposited: 27 Apr 2021 04:25
Last Modified: 27 Apr 2021 04:25
URI: http://repositori.lapan.go.id/id/eprint/664

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