Abstract
The influence of wave polarization on texture parameters of objects in radar images (RIs) is examined by calculations of the second-order statistics (the fractal dimension and the Haralick textural features) on the basis of polarimetric data acquired with the Spaceborne Imaging Radar-C/X-Band Synthetic Aperture Radar (SIR-C/X-SAR) system for two wavelengths of the C- and L-ranges. The variance analysis of the samples of fractal dimension values for natural forested and water objects have revealed no influence of polarization on the values before the speckle filtering; however, after speckle filtering, statistically valid differences have been found in the mean values of some pairs of samples. For sample pairs of the copolarizations VV–HH and cross polarizations HV–VH, a random nature of the differences observed in the mean fractal dimension values has been shown. This conclusion is also true for the Haralick textural features of a water object—the contrast, inverse moment, and entropy. Statistically valid differences in the mean values of the Haralick textural features for urban and water objects have been revealed both before and after speckle filtering. For a forested object, variance analysis shows that the polarization-dependent differences in the mean values of the textural feature samples are statistically unreliable.
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REFERENCES
Chapman, B., SIR-C/AIRSAR Data Conversion Guide, Pasadena: JPL, Cal. Inst. Technol., 1994.
Di Martino, G., Iodice, A., Riccio, D., Ruello, G., and Zinno, I., The effects of polarization on fractal dimension maps estimated from SAR data, Proc. PolInSAR-2013, 28 January–1 February 2013, ESA-ESRIN, Program A-bstract Book, Frascati, Italy, 2013, pp. 123–124.
Ferro, C.J. and Warner, T.A., Scale and texture in digital image classification, Photogramm. Eng. Remote Sens., 2002, vol. 68, no. 1, pp. 51–63.
Haralick, R.M., Shanmugam, K.S., and Dinstein, I., Textural features for image classification, IEEE Trans. Syst. Man Cybern., 1973, vol. 3, no. 6, pp. 610–621.
Kim, Y. and van Zyl, J., Comparison of forest parameter estimation techniques using SAR data, Proc. IGARSS’2001, vol. 3, pp. 1395–1397.
Kronberg, P., Fernerkundung der Erde: Grundlagen und Methoden des Remote Sensing in der Geologie, Enke, 1985; Moscow: Mir, 1988.
Lee, J.S., Grunes, M.R., and de Grandi, G., Polarimetric SAR speckle filtering and its implications for classification, IEEE Trans. Geosci. Remote Sens., 1999, vol. 37, no. 5, pp. 2363–2373.
Pentland, A.P., Fractal based description of natural scenes, IEEE Trans. Pattern Anal. Mach. Intell., 1984, vol. 6, pp. 661–674.
Rodionova, N.V., Influence of the number of brightness level gradations on texture signs of radar imagery, Issled. Zemli Kosmosa, 1994, no. 6, pp. 26–29.
Rodionova, N.V., The use of texture information in the interpretation of satellite images of ERS, Materialy Pyatogo Belorusskogo kosmicheskogo kongressa (Proceedings of the Fifth Belorussian Space Congress), Minsk: OIPI NAN Belarusi, 2011, vol. 2, pp. 12–16.
Rodionova, N.V., Effect of speckle noise filtering on statistical characteristics of polarimetric radar images, Issled. Zemli Kosmosa, 2005, no. 5, no. 34–43.
Singh, D. and Pant, T., Application of fractal dimension on PAL-SAR data, 38th COSPAR Sci.Assembly, 2010.
Smith, T.G., Lange, G.D., and Marks, W.B., Fractal methods and results in cellular morphology, J. Neurosci. Methods, 1996, vol. 69, pp. 1123–1126.
Ulaby, F.T., Kouyate, F., Brisco, B., and Lee Williams, T.H., Textural information in SAR images, IEEE Trans. Geosci. Remote Sens., 1986, vol. GE-24, no. 2, pp. 235–245.
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Rodionova, N.V. Influence of Wave Polarization on the Texture Characteristics of Objects in Radar Images. Izv. Atmos. Ocean. Phys. 55, 935–938 (2019). https://doi.org/10.1134/S000143381909041X
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DOI: https://doi.org/10.1134/S000143381909041X