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Practical Computation Acceleration for Large Size Single Image Filtering Based Haze Removal

机译:基于大尺寸的单图像滤波的雾度拆除实用计算加速

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The main defect of traditional filtering based image dehazing approaches is huge time consuming, especially for large size image haze removal. In the work, a serial of practical computation acceleration strategies for bilateral filtering based haze removal are proposed. Our approach strength lies in its wide practicability: better dehazing with very fast computation speed even for large size images. Since our approach requires less time consuming corresponding to less CPU load, it will be promising for some real time application, such as smart TV image enhancement.
机译:基于传统过滤的图像脱水方法的主要缺陷是巨大的耗时,特别是对于较大尺寸的图像雾度去除。在工作中,提出了一种串行的基于双边滤波的雾度去除的实际计算加速策略。我们的方法实力在于它的可观实用性:即使对于大尺寸的图像,更快的计算速度更好地脱脱。由于我们的方法需要对应于较少的CPU负载时耗费较少的时间,因此对于一些实时应用,这将是有希望的,例如智能电视图像增强。

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