Efficient, Blind, Spatially-Variant Deblurring for Shaken Images - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Book Sections Year : 2014

Efficient, Blind, Spatially-Variant Deblurring for Shaken Images


In this chapter we discuss modeling and removing spatially-variant blur from photographs. We describe a compact global parameterization of camera shake blur, based on the 3D rotation of the camera during the exposure. Our model uses three-parameter homographies to connect camera motion to image motion and, by assigning weights to a set of these homographies, can be seen as a generalization of the standard, spatially-invariant convolutional model of image blur. As such we show how existing algorithms, designed for spatially-invariant deblurring, can be "upgraded" in a straightforward manner to handle spatially-variant blur instead. We demonstrate this with algorithms working on real images, showing results for blind estimation of blur parameters from single images, followed by non-blind image restoration using these parameters. Finally, we introduce an efficient approximation to the global model, which significantly reduces the computational cost of modeling the spatially-variant blur. By approximating the blur as locally-uniform, we can take advantage of fast Fourier-domain convolution and deconvolution, reducing the time required for blind deblurring by an order of magnitude.
Fichier principal
Vignette du fichier
whyte13.pdf (8.56 Mo) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-01063814 , version 1 (13-09-2014)


  • HAL Id : hal-01063814 , version 1


Oliver Whyte, Josef Sivic, Andrew Zisserman, Jean Ponce. Efficient, Blind, Spatially-Variant Deblurring for Shaken Images. A. N. Rajagopalan; Rama Chellappa. Motion Deblurring: Algorithms and Systems, Cambridge University Press, 2014. ⟨hal-01063814⟩
111 View
611 Download


Gmail Facebook Twitter LinkedIn More