Navegar

Colección

Datos Estadísticas

Artículo

Estamos trabajando para incorporar este artículo al repositorio
Consulte el artículo en la página del editor
Consulte la política de Acceso Abierto del editor

Abstract:

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 stacks of binary images according to a set of thresholds. Each binary image is then filtered by a Boolean function, which characterizes the filter. Adaptive stack filters can be computed by training using a prototype (ideal) image and its corrupted version, leading to optimized filters with respect to a loss function. In this work we propose the use of training with selected samples for the estimation of the optimal Boolean function. We study the performance of adaptive stack filters when they are applied to speckled imagery, in particular to Synthetic Aperture Radar (SAR) images. This is done by evaluating the quality of the filtered images through the use of suitable image quality indexes and by measuring the classification accuracy of the resulting images. We used SAR images as input, since they are affected by speckle noise that makes classification a difficult task. © 2013 Elsevier B.V. All rights reserved.

Registro:

Documento: Artículo
Título:Speckle reduction with adaptive stack filters
Autor:Buemi, M.E.; Frery, A.C.; Ramos, H.S.
Filiación:Departamento de Computation, Facultad de Ciencias Exactes y Naturales, Universidad de Buenos Aires, Pabellón I, Buenos Aires, Argentina
LCCV and LaCCAN, CPMAT, Universidade Federal de Alagoas, BR 104 Norte km 97, 57072-970 Maceió, AL, Brazil
Palabras clave:Non-linear filters; SAR image filtering; Speckle noise; Stack filters; Bandpass filters; Binary images; Bins; Boolean functions; Nonlinear filtering; Radar imaging; Speckle; Synthetic aperture radar; Classification accuracy; Non linear; Optimized filters; SAR Images; Speckle noise; Speckle reduction; Stack filters; Synthetic aperture radar (SAR) images; Adaptive filters
Año:2014
Volumen:36
Número:1
Página de inicio:281
Página de fin:287
DOI: http://dx.doi.org/10.1016/j.patrec.2013.06.005
Título revista:Pattern Recognition Letters
Título revista abreviado:Pattern Recogn. Lett.
ISSN:01678655
Registro:https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_01678655_v36_n1_p281_Buemi

Referencias:

  • Astola, J., Kuosmanen, P., (1997) Fundamentals of Nonlinear Digital Filtering, , CRC Press, Boca Raton
  • Buemi, M.E., Mejail, M.E., Jacobo-Berlles, J., Gambini, J., Improvement in SAR image classification using adaptive stack filters (2007) Proceedings XX Brazilian Symposium on Computer Graphics and Image Processing (SIBGRAPI), pp. 263-270. , IEEE Computer Press
  • Buemi, M.E., Mejail, M., Jacobo, J., Frery, A.C., Ramos, H.S., Assessment of SAR image filtering using adaptive stack filters (2011) Proceedings 16th Iberoamerican Congress on Pattern Recognition (CIARP 2011), 7042, pp. 89-96. , Lecture Notes in Computer Science Springer, Pucón, Chile
  • Capstick, D., Harris, R., The effects of speckle reduction on classification of ERS SAR data (2001) International Journal of Remote Sensing, 22 (18), pp. 3627-3641. , DOI 10.1080/01431160110056506
  • Finn, S., Glavin, M., Jones, E., Echocardiographic speckle reduction comparison (2011) IEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control, 58 (1), pp. 82-101
  • Frery, A.C., Muller, H.-J., Yanasse, C.D.C.F., Sant'Anna, S.J.S., A model for extremely heterogeneous clutter (1997) IEEE Transactions on Geoscience and Remote Sensing, 35 (3), pp. 648-659. , PII S0196289297021037
  • Frost Victor, S., Stiles Josephine Abbott, Shanmugan, K.S., Holtzman Julian, C., Model for radar images and its application to adaptive digital filtering of multiplicative noise (1982) IEEE Transactions on Pattern Analysis and Machine Intelligence, PAMI-4 (2), pp. 157-166
  • Gao, G., Statistical modeling of SAR images: A survey (2010) Sensors, 10, pp. 775-795
  • Kuan, D.T., Sawchuk, A.A., Strand, T.C., Chavel, P., Adaptive restoration of images with speckle (1987) IEEE Transactions on Acoustics Speech and Signal Processing, 35 (3), pp. 373-383
  • Lee, J.-S., Refined filtering of image noise using local statistics (1981) Computer Graphics and Image Processing, 15 (4), pp. 380-389
  • Lee, J.S., Speckle suppression and analysis for synthetic aperture radar images (1986) Optical Engineering, 25, pp. 636-643
  • Lin, J.-H., Kim, Y.T., Fast algorithms for training stack filters (1994) IEEE Transactions on Signal Processing, 42 (3), pp. 772-781
  • Lin, H.-J., Sellke, T.M., Coyle, E.J., Adaptive stack filtering under the mean absolute error criterion (1990) IEEE Transactions on Acoustics, Speech and Signal Process, 38, pp. 938-954
  • Mejail, M.E., Jacobo-Berlles, J.C., 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. , DOI 10.1080/0143116021000053274
  • Moschetti, E., Palacio, M.G., Picco, M., Bustos, O.H., Frery, A.C., On the use of Lee's protocol for speckle-reducing techniques (2006) Latin American Applied Research, 36 (2), pp. 115-121
  • Nascimento, A.D.C., Cintra, R.J., Frery, A.C., Hypothesis testing in speckled data with stochastic distances (2010) IEEE Transactions on Geoscience and Remote Sensing, 48 (1), pp. 373-385
  • Oliver, C., Quegan, S., (1998) Understanding Synthetic Aperture Radar Images, , Artech House
  • Prasad, M.K., Stack filter design using selection probabilities (2005) IEEE Transactions on Signal Processing, 53 (3), pp. 1025-1037. , DOI 10.1109/TSP.2004.842208
  • Shi, G., Dong, W., Liu, Z., Design and implementation of stack filter based on immune memory clonal algorithms with hybrid computation (2005) 48th Midwest Symposium on Circuits and Systems, 2, pp. 1159-1162. , 7-10 August
  • Vasconcellos, K.L.P., Frery, A.C., Silva, L.B., Improving estimation in speckled imagery (2005) Computational Statistics, 20 (3), pp. 503-519. , DOI 10.1007/BF02741311
  • Wang, Z., Bovik, A.C., A universal image quality index (2002) IEEE Signal Processing Letters, 9 (3), pp. 81-84. , DOI 10.1109/97.995823, PII S1070990802048198
  • Yoo, J., Fong, K.L., Huang, J.-J., Coyle, E.J., Adams III, G.B., A fast algorithm for designing stack filters (1999) IEEE Transactions on Image Processing, 8 (8), pp. 772-781

Citas:

---------- APA ----------
Buemi, M.E., Frery, A.C. & Ramos, H.S. (2014) . Speckle reduction with adaptive stack filters. Pattern Recognition Letters, 36(1), 281-287.
http://dx.doi.org/10.1016/j.patrec.2013.06.005
---------- CHICAGO ----------
Buemi, M.E., Frery, A.C., Ramos, H.S. "Speckle reduction with adaptive stack filters" . Pattern Recognition Letters 36, no. 1 (2014) : 281-287.
http://dx.doi.org/10.1016/j.patrec.2013.06.005
---------- MLA ----------
Buemi, M.E., Frery, A.C., Ramos, H.S. "Speckle reduction with adaptive stack filters" . Pattern Recognition Letters, vol. 36, no. 1, 2014, pp. 281-287.
http://dx.doi.org/10.1016/j.patrec.2013.06.005
---------- VANCOUVER ----------
Buemi, M.E., Frery, A.C., Ramos, H.S. Speckle reduction with adaptive stack filters. Pattern Recogn. Lett. 2014;36(1):281-287.
http://dx.doi.org/10.1016/j.patrec.2013.06.005