Joint Defogging and Demosaicking

TL;DR

This paper introduces a joint defogging and demosaicking method that enhances image quality in foggy conditions by reducing artifacts and noise amplification, validated on both synthetic and real datasets.

Contribution

It proposes a novel combined defogging and demosaicking algorithm that improves visual quality and suppresses noise in foggy images, outperforming separate processing methods.

Findings

Enhanced defogging performance with fewer artifacts.

Suppressed noise amplification in distant scenes.

Validated effectiveness on synthetic and real datasets.

Abstract

Image defogging is a technique used extensively for enhancing visual quality of images in bad weather condition. 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 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 scene. In addition, we validate our theoretical analysis and observations for both synthesized datasets with ground truth fog-free images and natural scene datasets captured in a raw format.