Single Image Restoration for Participating Media Based on Prior Fusion

TL;DR

This paper introduces a novel image restoration technique for participating media like fog and turbid water, using a fusion of image priors and an image formation model to improve degraded image quality.

Contribution

It proposes a general method that fuses local contrast and color priors based on an image formation model, applicable to various participating media.

Findings

Effective restoration of underwater and foggy images

Demonstrated improvements over existing methods

Validated on a dataset with ground-truth images

Abstract

This paper describes a method to restore degraded images captured in a participating media -- fog, turbid water, sand storm, etc. Differently from the related work that only deal with a medium, we obtain generality by using an image formation model and a fusion of new image priors. The model considers the image color variation produced by the medium. The proposed restoration method is based on the fusion of these priors and supported by statistics collected on images acquired in both non-participating and participating media. The key of the method is to fuse two complementary measures --- local contrast and color data. The obtained results on underwater and foggy images demonstrate the capabilities of the proposed method. Moreover, we evaluated our method using a special dataset for which a ground-truth image is available.