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Adaptive UW Image Deblurring via Sparse Representation

: Farhadifard, Fahimeh; Radolko, Martin


Santos, Luis Paulo (Ed.) ; European Association for Computer Graphics -EUROGRAPHICS-:
Eurographics 2016. Short Papers : 2016, Lisbon, Portugal
Aire-la-Ville: Eurographics Association, 2016
ISSN: 1017-4656
European Association for Computer Graphics (Eurographics Annual Conference) <37, 2016, Lisbon>
Fraunhofer IGD ()
Guiding Theme: Visual Computing as a Service; Research Area: Computer vision (CV); computer vision; depth map; image enhancement; image processing

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.