Adaptive UW Image Deblurring via Sparse Representation

Farhadifard, Fahimeh; Radolko, Martin

Adaptive UW Image Deblurring via Sparse Representation

Files

041-044.pdf (3.45 MB)

Date

2016

Authors

Farhadifard, Fahimeh
Radolko, Martin

Publisher

The Eurographics Association

Abstract

We present an adaptive underwater (UW) image deblurring algorithm based on sparse representation where a blur estimation is used to guide the algorithm for the best image reconstruction. The strong blur in this medium is caused by forward scatter and is challenging since it increases by camera scene distance. It is a common practice to use methods such as dark channel prior to estimate the depth map, and use this information to improve the image quality. However, we found it not successful in the case of blur since these methods are based on haze phenomenon. We propose a simple but effective algorithm via sparse representation which establishes a blur strength estimation and uses this information for adaptive deblurring. Extensive experiments manifest the effectiveness of our method in case of small but challenging blur changes.

        @inproceedings{10.2312:egsh.20161010
,
booktitle = {EG 2016 - Short Papers
},
editor = {T. Bashford-Rogers and L. P. Santos
},
title = {{Adaptive UW Image Deblurring via Sparse Representation
}},
author = {Farhadifard, Fahimeh and 
Radolko, Martin
},
year = {2016
},
publisher = {The Eurographics Association
},
ISSN = {1017-4656
},
ISBN = {},
DOI = {10.2312/egsh.20161010
}
}