Título:
Estimating an images blur kernel using natural image statistics, and deblurring it : An analysis of the Goldstein-Fattal method
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Autor:
Anger, Jeremy
Facciolo, Gabriele
Delbracio, Mauricio
Facciolo, Gabriele
Delbracio, Mauricio
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Tipo de documento:
Artículo
Editor:
Palabras clave:
Descriptores:
Procesamiento de Señales
Año de publicación:
2018
Contenido:
Resumen:
Despite the significant improvement in image quality resulting from improvement in optical sensors and general electronics, camera shake blur significantly undermines the quality of hand-held photographs. In this work, we present a detailed description and implementation of the blur kernel estimation algorithm introduced by Goldstein and Fattal in 2012. Unlike most methods that attempt to solve an inverse problem through a variational formulation (e.g. through a Maximum A Posteriori estimation), this method directly estimates the blur kernel by modeling statistical irregularities in the power spectrum of blurred natural images. The adopted mathematical model extends the well-known power-law by contemplating the presence of dominant strong edges in particular directions. The blur kernel is retrieved from an estimation of its power spectrum, by solving a phase retrieval problem using additional constraints associated with the particular nature of camera shake blur kernels (e.g. non-negativity and small spatial support). Although the algorithm is conceptually simple, its numerical implementation presents several challenges. This work contributes to a detailed anatomy of the Goldstein and Fattal method, its algorithmic description, and its parameters.
Descripción:
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Editorial:
IPOL
EN:
Image Processing On Line, 8 (2018), pp. 282–304
Financiadores:
Citación:
Anger, J, Facciolo, G, Delbracio, M. “Estimating an Image's Blur Kernel Using Natural Image Statistics, and Deblurring it: An Analysis of the Goldstein-Fattal Method” Image Processing On Line, 8 (2018), pp. 282–304. https://doi.org/10.5201/ipol.2018.211
Citación:
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ISBN:
e-ISBN:
ISSN:
2105-1232
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Departamento académico:
Procesamiento de Señales
Grupo de investigación:
Tratamiento de Imágenes
Licencia:
Licencia Creative Commons Atribución – Compartir Igual (CC - By-SA)
Colecciones:
| Ficheros | Descripción | Tamaño | Formato | ||
|---|---|---|---|---|---|
| AFD18a.pdf | — | 6.67 MB | Adobe PDF |