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  • Title: Joint Defogging and Demosaicking.
    Author: Yeejin Lee, Hirakawa K, Nguyen TQ.
    Journal: IEEE Trans Image Process; 2017 Jun; 26(6):3051-3063. PubMed ID: 27893389.
    Abstract:
    Image defogging is a technique used extensively for enhancing visual quality of images in bad weather conditions. Even though defogging algorithms have been well studied, defogging performance is degraded by demosaicking artifacts and sensor noise amplification in distant scenes. In order to improve the visual quality of restored images, we propose a novel approach to perform defogging and demosaicking simultaneously. We conclude that better defogging performance with fewer artifacts can be achieved when a defogging algorithm is combined with a demosaicking algorithm simultaneously. We also demonstrate that the proposed joint algorithm has the benefit of suppressing noise amplification in distant scenes. In addition, we validate our theoretical analysis and observations for both synthesized data sets with ground truth fog-free images and natural scene data sets captured in a raw format.
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