A fully digital auto-focusing system based on point-spread function (PSF) estimation is proposed. To increase accuracy in estimating the PSF of the defocused image, the input image is subdivided, and the step responses of edge-containing subimages are averaged. The PSF, which results from out-of-focus blur, is estimated by differentiating the averaged step response along the appropriately estimated edge direction under the assumption that an image usually contains a piece-wise linear boundary between an object and background. By using the estimated PSF, the corresponding image restoration filter is realised, based on the constrained least squares approach.
Out-of-focus blur estimation and restoration for digital auto-focusing system
1998-06-11
3 pages
Article (Journal)
English
digital auto-focusing system , step responses , piecewise-linear techniques , step response , image restoration filter , constrained least squares approach , out-of-focus blur estimation , point-spread function estimation , estimation theory , edge-containing subimages , piece-wise linear boundary , least squares approximations , image restoration , defocused image , blur restoration , PWL boundary , focusing
Multichannel blind blur identification and image restoration [3545-161]
British Library Conference Proceedings | 1998
|A Simple Algorithm for Joint Blur Identification and Image Restoration
British Library Conference Proceedings | 1994
|Multiple blur of star image and the restoration under dynamic conditions
Online Contents | 2011
|Deep Kernel Estimation for Turbulent Blur Correction
IEEE | 2023
|