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Restoration of an atmospherically blurred image based on physical model fusion approach

机译:基于物理模型融合方法的大气模糊图像复原

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This paper proposes a new restoration method, only using the single image information, combining atmospheric physical model with fusion techniques to reduce the degradation of the image contrast in bad weather conditions caused by atmospheric aerosols, such as haze and fog. The basic idea of this method is to utilize physics-based model method instead of multi-sensors to generate a serial of virtual images, and then to fuse those virtual images into a high contrast image based on the wavelet fusion technique. In contrast to previous methods, our restoration technique is not only independent on predicted structure, distributions of scene reflectance, or detailed knowledge about the particular weather condition, but also adapt to the situation without a reference image or images with moving objects captured by a video camera. Experiments on different poor-contrast images demonstrate the availability of the proposed method in case of restoring the atmospherically blurred images.
机译:本文提出了一种仅使用单一图像信息的新恢复方法,将大气物理模型与融合技术相结合,以减少由大气气溶胶(例如雾霾和雾)引起的恶劣天气条件下图像对比度的下降。该方法的基本思想是利用基于物理学的模型方法代替多传感器来生成一系列虚拟图像,然后基于小波融合技术将这些虚拟图像融合为高对比度图像。与以前的方法相比,我们的恢复技术不仅独立于预测的结构,场景反射率的分布或有关特定天气状况的详细知识,而且还可以适应没有参考图像或视频捕获具有移动物体的图像的情况相机。在不同的对比度较差的图像上进行的实验表明,该方法在恢复大气模糊图像的情况下是可行的。

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