We present a simple and effective blind image deblurring method based on the dark
channel prior. Our work is inspired by the interesting observation that the dark channel of …

We show in this paper that the success of previous maximum a posterior (MAP) based blur
removal methods partly stems from their respective intermediate steps, which implicitly or …

We present a new algorithm for removing motion blur from a single image. Our method
computes a deblurred image using a unified probabilistic model of both blur kernel …

Blind deconvolution is the recovery of a sharp version of a blurred image when the blur
kernel is unknown. Recent algorithms have afforded dramatic progress, yet many aspects of …

Photographs taken in low-light conditions are often blurry as a result of camera shake, ie a
motion of the camera while its shutter is open. Most existing deblurring methods model the …

In blind deconvolution one aims to estimate from an input blurred image ya sharp image x
and an unknown blur kernel k. Recent research shows that a key to success is to consider …

In various learning-based image restoration tasks, such as image denoising and image
super-resolution, the degradation representations were widely used to model the …

We present an effective blind image deblurring algorithm based on the dark channel prior.
The motivation of this work is an interesting observation that the dark channel of blurred …

Image blur is caused by a number of factors such as motion, defocus, capturing light over the
non-zero area of the aperture and pixel, the presence of anti-aliasing filters on a camera …

We propose a simple yet effective L 0-regularized prior based on intensity and gradient for
text image deblurring. The proposed image prior is based on distinctive properties of text …