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Wavelet Thresholding-Based Despeckling of COSMO-SkyMed SAR Image

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Abstract

The selection of an efficient speckle filter for SAR imagery primarily depends upon a specific application of interest and statistical characteristics of the noise present in SAR datasets. The main goal of this study is to assess the performance of the two wavelet shrinkage-based filtering techniques (VISU shrink and SURE shrink) against two spatial adaptive filters (Enhanced Lee and Gamma MAP) and one non-local filter (NL-SAR) for the removal of speckle noise from high-resolution COSMO-SkyMed (CSK) SAR datasets. Before applying these filters to real CSK datasets, they are tested on synthetically generated speckled test datasets and benchmark simulated SAR datasets. Experimental analysis has been conducted on synthetically generated speckled datasets based on varying level of speckle noise introduced on test images. In case of benchmark datasets, numerous qualitative and quantitative measures are observed and evaluated. To find the best filter for real CSK data, a Pareto optimality concept has been used where the coefficient of variation is the parameter considered. From the findings, it is evident that VISU shrink-generated speckle filtering solution is non-dominated by all the other filtering solutions except NL-SAR-based speckle suppression in smooth areas. Considering the various user-defined situations of homogeneity and heterogeneity in the SAR scene, an overall performance index is formulated and VISU shrink performs the best in all user-defined conditions.

Zusammenfassung

Speckle-Reduzierung mittels Wavelet und Schwellenwert bei COSMO-SkyMed SARSzenen. Die Auswahl eines effizienten Speckle-Filters für SAR-Bilder hängt in erster Linie von der spezifischen Anwendung und von statistischen Merkmalen des in den SARDatensätzen vorhandenen Rauschens ab. Das wichtigste Ziel dieser Untersuchung ist die Bewertung der Leistung der beiden Waveletbasierten Filtertechniken (VISU-Shrink und SURE-Shrink) im Vergleich zu zwei räumlich-adaptiven Filtern (Enhanced Lee und Gamma MAP) und einem nicht-lokalen Filter (NL-SAR) zur Unterdrückung von Speckle-Rauschen in hochaufgelösten COSMOSkyMed (CSK) SAR-Datensätzen. Bevor diese Filter auf echte CSK-Datensätze angewendet werden, wurden sie an Datensätzen erprobt, die entweder synthetisch erzeugte Speckles enthielten oder zu simulierten Datensätzen vorhandener Benchmarks gehörten. Wir haben die Untersuchungen an synthetisch erzeugten mit Speckles versehenen Datensätzen durchgeführt und dabei unterschiedliche Intensitäten des Speckle-Rauschens erprobt. Im Falle der Benchmark-Datensätze wurden zahlreiche qualitative und quantitative Messungen durchgeführt. Um den besten Filter für die CSK-Daten zu finden, wurde die Pareto-Optimierung eingesetzt, bei der der Variationskoeffizient der entscheidende Parameter ist. Ergebnis der Untersuchung ist, dass die Leistung des VISU-Filters von keinem anderen erreicht wird, außer von der NL-SAR-basierten Speckle-Unterdrückung in texturarmen Bereichen. Unter der Berücksichtigung der Benutzeranforderung zu Homogenität und Heterogenität der SARSzenen wird ein "overall performance index" formuliert.

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Acknowledgements

Authors would like to thank Indian Space Research Organization (ISRO) for funding this research. They also want to thank Dr. Charles Deledalle for providing the MATLAB code of the NL-SAR filter and Image Processing Research Group (GRIP) of University of Naples Federico II, Naples, Italy for providing the benchmark simulated datasets. They also want to acknowledge Italian Space Agency (ASI) for providing the required CSK datasets over Dhanbad area. Finally, they want to thank anonymous reviewers and the associate editor for their valuable comments and helpful suggestions which greatly improved the quality of the manuscript.

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Authors and Affiliations

  1. Department of Electronics and Communication Engineering, University of Engineering and Management, Kolkata, India

    Tapas Kumar Dey

  2. Department of Mining Engineering, Indian Institute of Technology, Kharagpur, India

    Biswajit Samanta & Debashish Chakravarty

  3. Space Applications Centre, Indian Space Research Organization, Ahmedabad, India

    Arundhati Misra

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  1. Tapas Kumar Dey
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  2. Biswajit Samanta
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  4. Arundhati Misra
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Correspondence to Tapas Kumar Dey.

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Dey, T.K., Samanta, B., Chakravarty, D. et al. Wavelet Thresholding-Based Despeckling of COSMO-SkyMed SAR Image. PFG 88, 319–336 (2020). https://doi.org/10.1007/s41064-019-00089-6

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