An Analysis of Black Fill Artefacts Noise Removal on GRD Products Sentinel-1 Data

Haris Suka Dyatmika, Katmoko Ari Sambodo, Rahmat Arief


Synthetic Aperture Radar (SAR) is an active remote sensing satellite which is able to acquire cloud free images in all weather conditions. It is also capable of night time operation. Sentinel-1 data is one of SAR data which is good for monitoring natural resources in area with high cloud cover throughout the year. Processing the data until mosaic product needs good methods and right procedure. An highlight processes to remove noise through border of GRD data scene necessary to do because the processing chain from raw data into L1 GRD (Ground Range Detected) products were leading to artefacts at the near and far range image borders. The artefacts were not visible at a glance in the raw data but, observable clearly after performing mosaic a sets of data. Some methods to fix the problem are available to use such as common noise removal methods. This paper analysed methods to do noise removal i.e. using a tool in ESA’s provided Sentinel-1 software (Sentinel Application Platform - SNAP) and proposed noise removal method using simple thresholding and segmentation process. The mosaic products results from both method shown good results visually but the detailed histogram shown that the S-1 Remove GRD Border Noise results still have a very low value pixels in the black-fill area while the Random Noise Removal removed all of the noise. PSNR of raw data mosaic, GRD Border Noise and Random Noise Removal results sequentially 8.5, 18.6 and 19.7 dB indicated that Random Noise Removal get the highest similarity to reference data.


sentinel-1; Synthetic Aperture Radar (SAR); noise removal; ground range detected; border noise.

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European Space Agency, Sentinel-1: ESA’s Radar Observatory Mission for GMES Operational Services, ESA Communications, AG Noordwijk, The Netherlands, 2012.

M. Shimada and O. Isoguchi, “JERS-1 SAR mosaics of Southeast Asia using calibrated path images,†Int. J. Remote Sens., vol. 23, no. 7, pp. 1507–1526, 2002.

A. Smith, “SEASAT SAR IPF SEASAT Data and Processing Issues,†Phoenix Systems, Tech. Rep, 2014.

R. Piantanida, G. Hajduch, and J. Poullaouec, “Sentinel-1 Level 1 Detailed Algorithm Definition,†ESA, Tech. Rep, 2016.

H. Guillaume, “Masking “ No-value †Pixels on GRD Products generated by the Sentinel-1 ESA IPF,†ESA, Tech. Rep, 2015.

H. S. Dyatmika, K. Sambodo, M. Budiono, and Hendayani, “Noise removal using thresholding and segmentation for random noise Sentinel-1 data,†J. Phys. Conf. Ser., vol. 54, 2017.

D. L. Donoho, “De-Noising by Soft-Thresholding,†IEEE Trans. Inf. Theory, vol. 41, no. 3, pp. 613–627, 1995.

R. Yang, L. Yin, M. Gabbouj, J. Astola, and Y. Neuvo, “Optimal weighted median filtering under structural constraints,†IEEE Trans. Signal Process., vol. 43, no. 3, pp. 591–604, 1995.

A. Ben Hamza, P. L. Luque-Escamilla, J. Martínez-Aroza, and R. Román-Roldán, “Removing noise and preserving details with relaxed median filters,†J. Math. Imaging Vis., vol. 11, no. 2, pp. 161–177, 1999.

S. Saudia, J. Varghese, K. Nallaperumal, S. P. Mathew, A. J. Robin, and S. Kavitha, “Salt and pepper impulse detection and median based regularization using adaptive median filter,†IEEE Reg. 10 Annu. Int. Conf. Proceedings/TENCON, pp. 1–6, 2008.

S. Sharma, “Removal of Fixed Valued Impulse Noise by Improved Trimmed Mean Median Filter,†IEEE Int. Conf. Comput. Intell. Comput. Res., pp. 1–8, 2014.

F. P. P. d. Vries, “Estimation of the parameters used in the azimuth compression,†TNO Physics and Electronics Laboratory, Tech. Rep, 1991.

F. De Zan and A. M. Guarnieri, “TOPSAR: Terrain observation by progressive scans,†IEEE Trans. Geosci. Remote Sens., vol. 44, no. 9, pp. 2352–2360, 2006.

F. Fois, P. Hoogeboom, F. Le Chevalier, and A. Stoffelen, “Future Ocean Scatterometry: On the Use of Cross-Polar Scattering to Observe Very High Winds,†IEEE Trans. Geosci. Remote Sens., vol. 53, no. 9, pp. 5009–5020, 2015.

G. J. Van Zadelhoff, A. Stoffelen, P. W. Vachon, J. Wolfe, J. Horstmann, and M. Belmonte Rivas, “Retrieving hurricane wind speeds using cross-polarization C-band measurements,†Atmos. Meas. Tech., vol. 7, no. 2, pp. 437–449, 2014.

J. W. Sapp, S. O. Alsweiss, Z. Jelenak, P. S. Chang, S. J. Frasier, and J. Carswell, “Airborne Co-polarization and Cross-Polarization Observations of the Ocean-Surface NRCS at C-Band,†IEEE Trans. Geosci. Remote Sens., vol. 54, no. 10, pp. 5975–5992, 2016.

J. Na’am, J. Harlan, S. Madenda, and E. P. Wibowo, “The Algorithm of Image Edge Detection on Panoramic Dental X-Ray Using Multiple Morphological Gradient ( mMG ) Method,†Int. J. Adv. Sci. Eng. Inf. Technol., vol. 6, no. 6, pp. 1012–1018, 2016.

S. Caraiman and V. I. Manta, “Histogram-based segmentation of quantum images,†Theor. Comput. Sci., vol. 529, pp. 46–60, 2014.

N. Nabizadeh, N. John, and C. Wright, “Expert Systems with Applications Histogram-based gravitational optimization algorithm on single MR modality for automatic brain lesion detection and segmentation,†Expert Syst. Appl., vol. 41, no. 17, pp. 7820–7836, 2014.

Yuhendra, J. Tetuko, and S. Sumantyo, “Assessment of Multi-Temporal Image Fusion for Remote Sensing Application,†Int. J. Adv. Sci. Eng. Inf. Technol., vol. 7, no. 3, pp. 778–784, 2017.

S. J. Pittman and B. Costa, “Using Lidar Bathymetry and Boosted Regression Trees to Predict the Diversity and Abundance of Fish and Corals Using Lidar Bathymetry and Boosted Regression Trees to Predict the,†J. Coast. Res., no. 53, pp. 27–38, 2009.

C. Kotropoulos, “Rule-based face detection in frontal views,†IEEE Int. Conf. Acoust. Speech, Signal Process., vol. 4, pp. 2537–2540, 1997.

Z. Wang, A. C. Bovik, H. R. Sheikh, S. Member, E. P. Simoncelli, and S. Member, “Image Quality Assessment : From Error Visibility to Structural Similarity,†IEEE Trans. Image Process., vol. 13, no. 4, pp. 600–612, 2004.

V. Rajinikanth and M. S. Couceiro, “RGB Histogram based Color Image Segmentation Using Firefly Algorithm,†Procedia Comput. Sci., vol. 46, no. 2014, pp. 1449–1457, 2015.

M. Ghanbari, “Scope of validity of PSNR in image / video quality assessment,†Electron. Lett., vol. 44, no. 13, pp. 9–10, 2008.

D. K. Park, Y. S. Jeon, C. S. Won, S. Park, and S. Yoo, “A Composite Histogram for Image Retrieval,†2000 IEEE Int. Conf. Multimed. Expo, vol. 1, pp. 355–358, 2000.

N. Thomos, N. Thomos, S. Member, and N. V Boulgouris, “Optimized Transmission of JPEG2000 Streams Over Wireless Channels,†IEEE Trans. Image Process., vol. 15, no. 1, 2006.



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