Speckle reduction with adaptive stack filters
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 the...
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| Otros Autores: | , |
| Formato: | Capítulo de libro |
| Lenguaje: | Inglés |
| Publicado: |
2013
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| Acceso en línea: | Registro en Scopus DOI Handle Registro en la Biblioteca Digital |
| Aporte de: | Registro referencial: Solicitar el recurso aquí |
| LEADER | 02904caa a22003737a 4500 | ||
|---|---|---|---|
| 001 | PAPER-11432 | ||
| 003 | AR-BaUEN | ||
| 005 | 20230518204134.0 | ||
| 008 | 140217s2013 xx ||||fo|||| 00| 0 eng|d | ||
| 024 | 7 | |2 scopus |a 2-s2.0-84879713948 | |
| 040 | |a Scopus |b spa |c AR-BaUEN |d AR-BaUEN | ||
| 100 | 1 | |a Buemi, M.E. | |
| 245 | 1 | 0 | |a Speckle reduction with adaptive stack filters |
| 260 | |c 2013 | ||
| 270 | 1 | 0 | |m Buemi, M.E.; Departamento de Computación, Facultad de Ciencias Exactas y Naturales, Universidad de Buenosemail: mebuemi@dc.uba.ar |
| 506 | |2 openaire |e Política editorial | ||
| 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 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. |l eng | |
| 536 | |a Article in Press | ||
| 593 | |a Departamento de Computación, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Pabellón I, Buenos Aires, Argentina | ||
| 593 | |a LCCV and LaCCAN/CPMAT, Universidade Federal de Alagoas, BR 104 Norte km 97, 57072-970 Maceió, AL, Brazil | ||
| 690 | 1 | 0 | |a NON-LINEAR FILTERS |
| 690 | 1 | 0 | |a SAR IMAGE FILTERING |
| 690 | 1 | 0 | |a SPECKLE NOISE |
| 690 | 1 | 0 | |a STACK FILTERS |
| 700 | 1 | |a Frery, A.C. | |
| 700 | 1 | |a Ramos, H.S. | |
| 773 | 0 | |d 2013 |p Pattern Recogn. Lett. |x 01678655 |t Pattern Recognition Letters | |
| 856 | 4 | 1 | |u http://www.scopus.com/inward/record.url?eid=2-s2.0-84879713948&partnerID=40&md5=6854752d4f4ac0be6e715b15c00c3485 |y Registro en Scopus |
| 856 | 4 | 0 | |u https://doi.org/10.1016/j.patrec.2013.06.005 |y DOI |
| 856 | 4 | 0 | |u https://hdl.handle.net/20.500.12110/paper_01678655_v_n_p_Buemi |y Handle |
| 856 | 4 | 0 | |u https://bibliotecadigital.exactas.uba.ar/collection/paper/document/paper_01678655_v_n_p_Buemi |y Registro en la Biblioteca Digital |
| 961 | |a paper_01678655_v_n_p_Buemi |b paper |c PE | ||
| 962 | |a info:eu-repo/semantics/article |a info:ar-repo/semantics/artículo |b info:eu-repo/semantics/publishedVersion | ||
| 999 | |c 72385 | ||