Defocus Map Detection Using a Single Image

Juan Andrade

Producción científica: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

1 Cita (Scopus)

Resumen

The estimation of blurred regions is an important stage in several computer vision applications. In this paper an efficient training-free detector of local blurriness based on edge features is presented. Due to the intrinsic sparsity of edges in natural images a blur map is creating by using an approach based on the heat diffusion principle. A 2D point discrete Poisson solver is concatenated with a guided filter stage in order to create the blurring map. Experiments with images from two publicly available datasets validate the proposed method.

Idioma originalInglés
Título de la publicación alojadaProceedings - 2016 International Conference on Computational Science and Computational Intelligence, CSCI 2016
EditoresMary Yang, Hamid R. Arabnia, Leonidas Deligiannidis, Leonidas Deligiannidis
EditorialInstitute of Electrical and Electronics Engineers Inc.
Páginas777-780
Número de páginas4
ISBN (versión digital)9781509055104
DOI
EstadoPublicada - 17 mar. 2017
Publicado de forma externa
Evento2016 International Conference on Computational Science and Computational Intelligence, CSCI 2016 - Las Vegas, Estados Unidos
Duración: 15 dic. 201617 dic. 2016

Serie de la publicación

NombreProceedings - 2016 International Conference on Computational Science and Computational Intelligence, CSCI 2016

Conferencia

Conferencia2016 International Conference on Computational Science and Computational Intelligence, CSCI 2016
País/TerritorioEstados Unidos
CiudadLas Vegas
Período15/12/1617/12/16

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