Abstract
This paper deals with the identification and elimination of ground echoes in radar images using their textural features. The images collected in Setif (Algeria) by a non Doppler radar, are processed. Two kinds of texture-based techniques have been considered, consisting in calculating either the histograms of their sum and difference or the pattern recognition. Energy and local homogeneity are found to be the textural parameters that clearly separate the precipitation and ground echoes. To get only the rainfall echoes, the resulting template is applied to each of the raw radar images and the filtering is improved by removing the residual clutter with pattern recognition. This method allows as to completely removing the ground clutter with minimal alterations of the rain echoes with reduced calculation time. It has the advantages of effectiveness and simplicity. However, when there is overlap of precipitation echoes with the ground echoes, significant small cells may occur. In this case, these cells are restored by interpolating from neighboring pixels with a regularization function. The application of this optimization algorithm of filtered images can effectively reproduce true structure of clouds. The radar images can be processed in real-time because the computation time needed by these techniques is small.
Article PDF
Similar content being viewed by others
Avoid common mistakes on your manuscript.
References
Chapman, R.N.: Development of sizing nomograms for stand-alone photovoltaic/storage systems. Sol. Eng. 43, 71–76 (1989)
Renaut, D.: Les satellites météorologiques. La Météorologie 45, 33–37 (2004)
Keeler, R.J., Passarelli, R.E.: Signal processing for atmospheric radars. In: Lenschow, D.H. (ed.): Radar Probing and Measurement of the Planetary Boundary Layer, pp. 199–229. American Meteorological Society, Boston (1986)
Serafin, R.J.: Meteorological radar. In: Skolnic, M. (ed.): Radar Handbook, 2nd ed, pp. 23.1–23.28. Mc Graw-Hill, New York (1990)
Sauvageot, H.: Radar Meteorology. Artech House, Boston (1992)
Taylor, J.W.: Receivers. In: Skolnik, M.I. (ed.): Radar Handbook, 2nd ed, pp. 3.1–3.54. McGraw-Hill, New York (1990)
Darricau, J.: Physique et théorie du radar, T.2: Principes et performances de base, Sodipe, Paris (1993)
Meischner, P.: Weather Radar: Principles and Advanced Applications. Springer, Berlin (2005)
Haddad, B., Adane, A., Sauvageot, H., Sadouki, L., Naili, R.: Identification and filtering of rainfall and ground radar echoes using textural features. Int. J. Remote. Sens. 25(21), 4641–4656 (2004)
Haralick, R.M., Shanmugam, K., Dinstein, I.: Textural features for image classification. IEEE Trans. Syst. Man Cybern. SMC-3(6), 610–621 (1973)
Weszka, J.S., Dyer, C.R., Rosenfeld, A.: Comparative study of texture measures for terrain classification. IEEE Trans. Syst. Man Cybern. SM-6, 269–285 (1976)
Unser, M.: Sum and difference histograms for texture classification. IEEE Trans. Pattern. Anal. Mach. Intell. PAMI-8(1), 118–125 (1986)
Chen, D.W., Sengupta, S.K., Welch, R.M.: Cloud field classification based upon high spatial resolution textural features, simplified vector approaches. J. Geoph. Res. 94–D12, 749–765 (1989)
Wang, L., He, D.C.: A new statistical approach for texture analysis. Photogramm. Eng. Remote. Sens. 56(1), 61–66 (1990)
Ameur, Z., Ameur, S., Adane, A., Sauvageot, H., Bara, K.: Cloud classification using the textural features of Meteosat images. Int. J. Remote Sens. 25(21), 4491–4503 (2004)
Raaf, O., Adane, A.: Image-filtering techniques for meteorological radar. In: International Symposium on Industrial Electronics, IEEE ISIE08, Cambridge (2008)
Bregman, L.M.: The relaxation method of finding the common points of convex sets and its application to the solution of problems in convex optimization. USSR Comput. Math. Math. Phys. 7, 200–217 (1967)
Rudin, L.I., Osher, S., Fatemi, E.: Nonlinear total variation based noise removal algorithms. Phys. D 60, 259–268 (1992)
Goldstein, T., Osher, S.: The Split Bregman method for l1-regularized problems. SIAM J. Imaging Sci. 2(2), 323–343 (2009)
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Raaf, O., Adane, A. Image-Filtering and Optimization of Rainy Cells. J Math Model Algor 13, 355–369 (2014). https://doi.org/10.1007/s10852-014-9252-1
Received:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s10852-014-9252-1