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A Fuzzy Logic Method for Extraction of Geographic Objects from IKONOS Imagery


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DOI: https://doi.org/10.15866/irecos.v10i4.4907

Abstract


A high resolution satellite image is characterized by detailed geographical information offered. However, the heterogeneity disrupt a processing image, whose the principle object is transformation into geographic card; which is until now carry out by classic operations. The present  paper propose a new methodology of geographic objects identification from multispectral image, which combine between colored composition and radiometric characteristic of geographic classes, the mathematical morphology in order to solve over segmentation; the most problem of high resolution imagery, followed by an oriented segmentation and a fuzzy logic classification based on the formulation of some observations into decisions rules. We focus our study on IKONOS high resolution images on some areas of Algeria.
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Keywords


HSR Satellite Images; Mathematical Morphology; Region Growing; Fuzzy Logic; Decision Rules

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References


Poulain, V., Optic and radar high resolution image fusion to updating map databases, Ph.D. Thesis, National Polytechnic Institute, Toulouse, France, 2010.

Dheepa, G., Sukumaran, S., Hybrid fusion technique using dual tree complex wavelet transform for satellite remote sensor images, (2014) International Review on Computers and Software (IRECOS), 9 (9), pp. 1560-1567.
http://dx.doi.org/10.15866/irecos.v9i9.3003

Shackelford, A.K. and Davis, C.H., A combined fuzzy pixel-based and object based approach for classification of high-resolution multispectral data over urban areas,(2003) IEEE transaction on geosciences and remote sensing, 41(10), pp. 2354-2363.
http://dx.doi.org/10.1109/tgrs.2003.815972

Liu, Z. J., Wang, J., and Liu, W. P., Building extraction from high resolution imagery based on multi-scale object oriented classification and probabilistic Hough transform, (2005) International Geoscience and Remote Sensing Symposium (IGARSS'05. Proceedings), 25-29 July 2005 .Seoul: IEEE, 2250 – 2253.
http://dx.doi.org/10.1109/igarss.2005.1525421

Zhang, Y., Optimisation of building detection in satellite images by combining multispectral classification and texture filtering, (1999) ISPRS Journal of photogrammetry and remote sensing, 54(1), pp. 50-60.
http://dx.doi.org/10.1016/s0924-2716(98)00027-6

Sheeren, D., Lefevre, S., and Weber, J., La morphologie mathématique binaire pour l’extraction automatique des bâtiments dans les images THRS. (2007) Revue internationale de Géomatique, 17(3-4), pp. 333-352
http://dx.doi.org/10.3166/geo.17.333-352

Goutsias, J., Vincent, L., and Bloomberg, D.S., Mathematical morphology and its applications to image and signal processing. New York: Kluwer academic, 2002.
http://dx.doi.org/10.1007/b117970

Gastellu, E.J.P., Acquisition et traitement d’image numérique [online] (2008). University Paul Sabatier, IUT - Departement of Physic Mesures. Available from: http://www.cesbio.ups-tlse.fr/data_all/pdf/TI08.pdf [Accessed Avril 2008].

Dougherty, Edward R., and Jaakko Astola, An intoduction to nonlinear image processing. Bellingham, Washington: The international society for optical engineering, 1994.
http://dx.doi.org/10.1007/978-1-4615-3148-7

Xiangyun, H., Vincent, T.C., and Bjorn, P., Automatic segmentation of high-resolution satellite imagery by integrating texture, intensity, and color features, 2005 Photogrammetric engineering and remote sensing, 71(12), 1399–1406.
http://dx.doi.org/10.14358/pers.71.12.1399

Wang, S., and Wang, A., Segmentation of high-resolution satellite imagery based on feature combination. (2008)The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XXXVII (B4), 1223-1228.

Trias-Sanz, R., Stamon, G., and Louchet, J., Using colour, texture, and hierarchial segmentation for high-resolution remote sensing, (2008) ISPRS Journal of Photogrammetry & Remote Sensing, 63 (2), 156–168.
http://dx.doi.org/10.1016/j.isprsjprs.2007.08.005

Tian, J., and Chen, M., Optimization in multi-scale segmentation of high- resolution satellite images for artificial feature recognition, (2007) International Journal of Remote Sensing, 28(20), 4625-4644.
http://dx.doi.org/10.1080/01431160701241746

Suganthi, G., Korah, R., Fuzzy segmentation and feature extraction for an efficient identification of mine-like objects, (2014) International Review on Computers and Software (IRECOS), 9 (7), pp. 1195-1200.

McNeill, F.M., and Ellen Thro, Fuzzy Logic A Practical Approach. Ap Professional, Boston:ACADEMIC PRESS, 1994.

Zhi-Hang, T., Bei-Ping, T., Han, Y., Yi-Jie, L., Xiang-Ling, L., Wen-Bin, T., Hai-Bin, W., A new pattern recognition method based on nonlinear support vector machine, (2013) International Review on Computers and Software (IRECOS), 8 (1), pp. 262-266.


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