Blind image deblurring using class-adapted image priors

09/06/2017
by   Marina Ljubenović, et al.
0

Blind image deblurring (BID) is an ill-posed inverse problem, usually addressed by imposing prior knowledge on the (unknown) image and on the blurring filter. Most of the work on BID has focused on natural images, using image priors based on statistical properties of generic natural images. However, in many applications, it is known that the image being recovered belongs to some specific class (e.g., text, face, fingerprints), and exploiting this knowledge allows obtaining more accurate priors. In this work, we propose a method where a Gaussian mixture model (GMM) is used to learn a class-adapted prior, by training on a dataset of clean images of that class. Experiments show the competitiveness of the proposed method in terms of restoration quality when dealing with images containing text, faces, or fingerprints. Additionally, experiments show that the proposed method is able to handle text images at high noise levels, outperforming state-of-the-art methods specifically designed for BID of text images.

READ FULL TEXT
research
05/23/2016

Image Restoration with Locally Selected Class-Adapted Models

State-of-the-art algorithms for imaging inverse problems (namely deblurr...
research
02/12/2016

Image Restoration and Reconstruction using Variable Splitting and Class-adapted Image Priors

This paper proposes using a Gaussian mixture model as a prior, for solvi...
research
10/23/2017

Accelerating GMM-based patch priors for image restoration: Three ingredients for a 100× speed-up

Image restoration methods aim to recover the underlying clean image from...
research
03/11/2022

TAPE: Task-Agnostic Prior Embedding for Image Restoration

Learning an generalized prior for natural image restoration is an import...
research
03/20/2023

Inverse problem regularization with hierarchical variational autoencoders

In this paper, we propose to regularize ill-posed inverse problems using...
research
04/06/2018

Adaptive Quantile Sparse Image (AQuaSI) Prior for Inverse Imaging Problems

Inverse problems play a central role for many classical computer vision ...
research
08/13/2014

Gradient Distribution Priors for Biomedical Image Processing

Ill-posed inverse problems are commonplace in biomedical image processin...

Please sign up or login with your details

Forgot password? Click here to reset