[IPOL announce] new article: Breaking down Polyblur: Fast Blind Correction of Small Anisotropic Blurs

[announcements about the IPOL journal]

A new article is available in IPOL: https://www.ipol.im/pub/art/2022/405/

Thomas Eboli, Jean-Michel Morel, and Gabriele Facciolo,
Breaking down Polyblur: Fast Blind Correction of Small Anisotropic Blurs,
Image Processing On Line, 12 (2022), pp. 435–456.
https://doi.org/10.5201/ipol.2022.405

Abstract
Polyblur is a two stage blind deblurring technique for removing 
small-sized blurs, like small camera shake or the lens point-spread 
function, proposed in 2021 by Delbracio et al. First, the blur is 
modeled with a zero-mean anisotropic Gaussian kernel whose parameters 
are rapidly estimated from the oriented blurry image gradients. Second, 
a sharp estimate is obtained by applying an approximate deconvolution 
filter, which is designed as a polynomial function of the estimated 
blurring kernel. Since in practice true blurs are not exactly Gaussian 
filters, the residual blur is gradually removed by repeating this 
two-stage procedure. Because it relies only on simple image 
manipulations, Polyblur is a quick blind deblurring technique, running 
in a fraction of a second on a smartphone. In this presentation, we 
analyze its key ingredients, showcase several use cases on real images, 
and provide Numpy and Pytorch implementations.