论文标题
基于局部对比度增强方法的通用飞行算法
A General-Purpose Dehazing Algorithm based on Local Contrast Enhancement Approaches
论文作者
论文摘要
Dhazing在图像处理和计算机视觉社区中，这是增强在有雾条件下拍摄的图像的任务。为了更好地理解这种类型的算法，我们在本文档中介绍了一种脱掩护方法，适用于几种局部对比度调整算法。我们将其基于两个过滤器。第一个过滤器是通过标准化步骤构建的，其中一些统计技巧代表局部对比度改进算法。因此，它可以在CPU和GPU上用于实时应用程序。我们希望我们的方法能为社区中的新想法打开大门。我们方法的其他优点首先是它不需要培训，因此它不需要其他优化处理。此外，它可以用作许多视觉任务的预处理或后处理步骤。此外，它不需要将问题转换为物理解释，最后是非常快。这个融化算法的家族非常简单，但是与最新的算法相比，它不仅基于视觉评估，而且基于客观标准，都显示出令人鼓舞的结果。
Dehazing is in the image processing and computer vision communities, the task of enhancing the image taken in foggy conditions. To better understand this type of algorithm, we present in this document a dehazing method which is suitable for several local contrast adjustment algorithms. We base it on two filters. The first filter is built with a step of normalization with some other statistical tricks while the last represents the local contrast improvement algorithm. Thus, it can work on both CPU and GPU for real-time applications. We hope that our approach will open the door to new ideas in the community. Other advantages of our method are first that it does not need to be trained, then it does not need additional optimization processing. Furthermore, it can be used as a pre-treatment or post-processing step in many vision tasks. In addition, it does not need to convert the problem into a physical interpretation, and finally that it is very fast. This family of defogging algorithms is fairly simple, but it shows promising results compared to state-of-the-art algorithms based not only on a visual assessment but also on objective criteria.
