Aggregation functions to combine RGB color channels in stereo matching

In this paper we present a comparison study between different aggregation functions for the combination of RGB color channels in stereo matching problem. We introduce color information from images to the stereo matching algorithm by aggregating the similarities of the RGB channels which are calculat...

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Detalles Bibliográficos
Autores: Galar Idoate, Mikel, Jurío Munárriz, Aránzazu, López Molina, Carlos, Sanz Delgado, José Antonio, Paternain Dallo, Daniel, Bustince Sola, Humberto
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2013
País:España
Institución:Universidad San Jorge (USJ)
Repositorio:Academica-e. Repositorio Institucional de la Universidad Pública de Navarra
OAI Identifier:oai:academica-e.unavarra.es:2454/21074
Acceso en línea:https://hdl.handle.net/2454/21074
Access Level:acceso abierto
Palabra clave:Image processing
Machine vision
Vision, color and visual optics
Descripción
Sumario:In this paper we present a comparison study between different aggregation functions for the combination of RGB color channels in stereo matching problem. We introduce color information from images to the stereo matching algorithm by aggregating the similarities of the RGB channels which are calculated independently. We compare the accuracy of different stereo matching algorithms and aggregation functions. We show experimentally that the best function depends on the stereo matching algorithm considered, but the dual of the geometric mean excels as the most robust aggregation.