联合去雾和去马赛克
Joint Defogging and Demosaicking
摘要：
图像去雾是在恶劣天气条件下提高图像视觉质量的一种常用技术。尽管去雾算法已经得到了很好的研究，但去马赛克伪影和远处场景中的传感器噪声放大会降低去雾性能。为了提高恢复图像的视觉质量，我们提出了一种新的方法，同时进行去雾和去马赛克。我们得出结论，更好的去雾性能与较少的文物，可以实现时，去雾算法与去马赛克算法相结合的同时。我们还证明了所提出的联合算法具有抑制噪声放大的好处，在遥远的场景。此外，我们验证了我们的理论分析和观察与地面真实无雾图像和自然场景的原始格式捕获的数据集的合成数据集。
英文摘要：
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.
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