Filtros Robustos RM–KNN con Diferentes Funciones de Influencia para Supresión de Ruido Impulsivo en Imágenes Digitales
Robust RM–KNN Filters with Different Influence Functions for Removal of Impulsive Noise in Digital Images
Francisco Gallegos1, Volodymyr Ponomaryov2, Oleksiy Pogrebnyak3 y Luis Niño de Rivera2
1 Escuela Superior de Ingeniería Mecánica y Eléctrica, U.P.A.L.M, Zacatenco Av. IPN s/n, Col. Lindavista, C.P. 07738, México, D.F. E–mail: fcogf@hotmail.com
2 Escuela Superior de Ingeniería Mecánica y Eléctrica, U.P. Culhuacán del IPN Av. Sta. Ana 1000, Col. San Francisco Culhuacán, C.P. 04430, México, D.F. E–mail: vponomar@ipn.mx
]]> 3 Centro de Investigación en Computación del IPN Av. Juan de Dios Bátiz s/n Col. Lindavista C.P. 07738, México D.F. E–mail: olek@cic.ipn.mx
Artículo recibido en Diciembre 12, 2002
Aceptado en Marzo 15, 2003
Resumen
Presentamos la implementación de filtros robustos para imágenes con supresión de ruido impulsivo y preservación de detalles. Los esquemas de filtrado usan una técnica similar al filtro KNN para proveer la preservación de detalles finos y la combinación de estimadores–M con el estimador de la mediana o Wilcoxon proveen la supresión de ruido impulsivo. Usamos diferentes tipos de funciones de influencia en el estimador–Mpara proveer una mejor supresión de ruido impulsivo. El filtrado de secuencias de vídeo corrompidas con ruido impulsivo demuestra que los métodos propuestos potencialmente proveen una solución para mejorar la calidad de las transmisiones de TV/Vídeo. La eficiencia de los filtros propuestos fue evaluada por numerosas simulaciones. La implementación de los filtros propuestos fue realizada en tiempo real mediante el uso del DSP TMS320C6701.
Palabras Clave: Filtros de orden estadístico, filtros RM–KNN, DSP TMS320C6701.
Abstract
]]> We present the implementation of robust image filtering for impulsive noive suppression with detail preservation. The filtering schemes use a similar to KNN filter technique to provide fine detail preservation and the redescending M–estimators combined with the median or Wilcoxon estimator to provide impulsive noise rejection. We use different types of influence functions in the M–estimator to provide better impulsive noise suppression. The filtration of image sequences corrupted by impulsive noise demonstrates that the proposed methods potentially could provide a solution to quality TV/Video transmission. The efficiency of the proposed filters has been evaluated by numerous simulations. The implementation of proposed filters was realized in real–time by means of use of DSP TMS320C6701.Keywords: Order Statistics Filters, RM–KNN filters, DSP TMS320C6701.
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Agradecimientos
Los autores dan las gracias al Instituto Politécnico Nacional y al programa PROMEP SUPERA por los apoyos brindados.
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