Improvement in SAR image classification using adaptive stack filters

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Stack filters are a special case of non-linear filters. They have a good performance for filtering images with different types of noise while preserving edges and details. A stack filter decomposes an input image into several binary images according to a set of thresholds. Each binary image is filte...

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Detalles Bibliográficos
Autor principal: Buemi, M.E
Otros Autores: Mejail, M., Jacobo, J., Gambini, J.
Formato: Acta de conferencia Capítulo de libro
Lenguaje:Inglés
Publicado: 2007
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RADAR
Acceso en línea:Registro en Scopus
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Biblioteca Central Dr. Luis F. Leloir (FCEN) de Universidad de Buenos Aires
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100 1 |a Buemi, M.E. 
245 1 0 |a Improvement in SAR image classification using adaptive stack filters 
260 |c 2007 
270 1 0 |m Buemi, M. E.; Universidad de Buenos Aires, Facultad de Ciencias Exactas Y Naturales, Pabellón I, C1428EGA Buenos Aires, Argentina; email: mebuemi@dc.uba.ar 
506 |2 openaire  |e Política editorial 
504 |a Astola, J., Kuosmanen, P., (1997) Fundamentals of Nonlinear Digital Filtering, , CRC Press, Boca Raton 
504 |a Coyle, E.J., Lin, J.-H., Gabbouj, M., Optimal stack filtering and the estimation and structural approaches to image processing (1989) IEEE Trans. Acoust., Speech, Signal Processing, 37, pp. 2037-2066 
504 |a Coyle, J., Lin, J.-H., Stack filters and the mean absolute error criterion (1988) IEEE Trans. Acoust., Speech, Signal Processing, 36, pp. 1244-1254 
504 |a Dellamonica Jr., D., Silva, P.J.S., Humes Jr., C., Hirata, N.S.T., Barrera, J., An exact algorithm for optimal mae stack filter design (2007) Image Processing, IEEE Transactions on, 16 (2). , 453-462, Feb 
504 |a Diaz, D., Paredes, J., Fpga implementation of a new family of stack filters (2004) Devices, Circuits and Systems, 2004. Proceedings of the Fifth IEEE International Caracas Conference on, 1, pp. 152-157. , 3-5 Nov 
504 |a Frery, A.C., Correia, A.H., Rennó, C.D., Freitas, C.C., Jacobo-Berlles, J., Mejail, M.E., Vasconcellos, K.L.P., Models for synthetic aperture radar image analysis (1999) Resenhas (IME-USP), 4 (1), pp. 45-77 
504 |a Frery, A.C., Müller, H.-J., Yanasse, C.C.F., Sant'Anna, S.J.S., A model for extremely heterogeneous clutter (1996) IEEE Transactions on Geoscience and Remote Sensing, 35 (3), pp. 648-659. , May 
504 |a Goodman, J.W., Some fundamental properties of speckle (1976) Journal of the Optical Society of America, 66, pp. 1145-1150 
504 |a Lin, H.J., Sellke, T.M., Coyle, E.J., Adaptive stack filtering under the mean absolute error criterion (1990) IEEE Trans. Acoust., Speech, Signal Process, 38, pp. 938-954 
504 |a (1981) J.-S. Lee. Refined filtering of image noise using local statistics, 15 (4), pp. 380-389. , Apr 
504 |a Lin, J.-H., Kim, Y., Fast algorithms for training stack filters IEEE Trans. Signal Processing, 42 (3), pp. 772-781,4-1994 
504 |a Lopes, A., Nezry, E., Touzi, R., Laur, H., Structure detection and statistical adaptive speckle filtering in SAR images (1993) International Journal of Remote Sensing, 14 (9), pp. 1735-1758 
504 |a Mejail, M.E., Jacobo-Berlles, J., Frery, A.C., Bustos, O.H., Classification of SAR images using a general and tractable multiplicative model (2003) International Journal of Remote Sensing, 24 (18), pp. 3565-3582 
504 |a Oliver, C., Quegan, S., (1998) Understanding synthetic aperture radar images, , Artech House 
504 |a J. Paredes and G. Arce. Stack filters, stack smoothers, and mirrored threshold decomposition. Signal Processing, IEEE Transactions on [see also Acoustics, Speech, and Signal Processing, IEEE Transactions on], 47(10):2757-2767, Oct. 1999; M. Prasad. Stack filter design using selection probabilities. Signal Processing, IEEE Transactions on [see also Acoustics, Speech, and Signal Processing, IEEE Transactions on], 53(3):1025-1037, Mar 2005; G. Shi, W. Dong, and Z. Liu. Design and implementation of stack filter based on immune memory clonal algorithms with hybrid computation. In Circuits and Systems, 2005. 48th Midwest Symposium on, pages 1159-1162Vol.2, 7-10 Aug. 2005; Smith, D., Speckle Reduction and Segmentation of SAR Images International Journal of Remote Sensing, 17 (11). , 2043-205, 199 
504 |a Frost, K.S., Stiles, J.A., A model for radar images and its application to adaptive digital filtering of multiplicative noise (1982) IEEE Transactions on Pattern Analysis and Machine Intelligence, 4, pp. 157-166. , mar 
504 |a Wendt, P., Coyle, E.J., Gallangher, J.N.C., Stack filters (1986) IEEE Trans. Acoust. Speech Signal Processing, 34 (898-911), p. 8 
504 |a Yoo, J., Fong, K.L., Huang, J.J., Coyle, E.J., III. A fast algorithm for designing stack filters IEEE Trans.on image processing, 8 (8), pp. 772-781,8-1999 
520 3 |a Stack filters are a special case of non-linear filters. They have a good performance for filtering images with different types of noise while preserving edges and details. A stack filter decomposes an input image into several binary images according to a set of thresholds. Each binary image is filtered by a Boolean function. The Boolean function that characterizes an adaptive stack filter is optimal and is computed from a pair of images consisting of an ideal noiseless image and its noisy version. In this work the behavior of adaptive stack filters is evaluated for the classification of Synthetic Aperture Radar (SAR) images, which are affected by speckle noise. With this aim it was carried out experiment in which simulated and real images are generated and then filtered with a stack filter trained with one of them. The results of their Maximum Likelihood classification are evaluated and then are compared with the results of classifying the images without previous filtering. © 2007 IEEE.  |l eng 
593 |a Universidad de Buenos Aires, Facultad de Ciencias Exactas Y Naturales, Pabellón I, C1428EGA Buenos Aires, Argentina 
690 1 0 |a BINARY IMAGES 
690 1 0 |a BOOLEAN FUNCTIONS 
690 1 0 |a COMPUTATIONAL GEOMETRY 
690 1 0 |a COMPUTER GRAPHICS 
690 1 0 |a DIGITAL IMAGE STORAGE 
690 1 0 |a IMAGE ANALYSIS 
690 1 0 |a IMAGE CLASSIFICATION 
690 1 0 |a IMAGE PROCESSING 
690 1 0 |a IMAGING SYSTEMS 
690 1 0 |a SYNTHETIC APERTURE RADAR 
690 1 0 |a SYNTHETIC APERTURES 
690 1 0 |a INPUT IMAGES 
690 1 0 |a LINEAR FILTERS 
690 1 0 |a NOISELESS IMAGES 
690 1 0 |a NOISY VERSIONS 
690 1 0 |a REAL IMAGES 
690 1 0 |a SPECKLE NOISES 
690 1 0 |a STACK FILTERS 
690 1 0 |a IMAGE ENHANCEMENT 
650 1 7 |2 spines  |a RADAR 
700 1 |a Mejail, M. 
700 1 |a Jacobo, J. 
700 1 |a Gambini, J. 
711 2 |c Belo Horizonte, MG  |d 7 October 2007 through 10 October 2007  |g Código de la conferencia: 72737 
773 0 |d 2007  |h pp. 263-270  |p Proc. SIBGRAPI - Braz. Symp. Comput. Graphics Image Process.  |n Proceedings of SIBGRAPI 2007 - 20th Brazilian Symposium on Computer Graphics and Image Processing  |z 0769529968  |z 9780769529967  |t 20th Brazilian Symposium on Computer Graphics and Image Processing, SIBGRAPI 2007 
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856 4 0 |u https://doi.org/10.1109/SIBGRAPI.2007.40  |y DOI 
856 4 0 |u https://hdl.handle.net/20.500.12110/paper_07695299_v_n_p263_Buemi  |y Handle 
856 4 0 |u https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_07695299_v_n_p263_Buemi  |y Registro en la Biblioteca Digital 
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