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Weighted Guided Image Filtering

机译:加权引导图像过滤

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摘要

It is known that local filtering-based edge-preserving smoothing techniques suffer from halo artifacts. In this paper, a weighted guided image filter (WGIF) is introduced by incorporating an edge-aware weighting into an existing guided image filter (GIF) to address the problem. The WGIF inherits advantages of both global and local smoothing filters in the sense that: 1) the complexity of the WGIF is for an image with pixels, which is same as the GIF and 2) the WGIF can avoid halo artifacts like the existing global smoothing filters. The WGIF is applied for single image detail enhancement, single image haze removal, and fusion of differently exposed images. Experimental results show that the resultant algorithms produce images with better visual quality and at the same time halo artifacts can be reduced/avoided from appearing in the final images with negligible increment on running times.
机译:众所周知,基于局部滤波的边缘保持平滑技术遭受光晕伪像的困扰。在本文中,通过将边缘感知加权合并到现有的导引图像滤波器(GIF)中来引入加权导引图像滤波器(WGIF),以解决该问题。 WGIF在以下方面继承了全局和局部平滑滤波器的优点:1)WGIF的复杂度适用于具有像素的图像,与GIF相同; 2)WGIF可以避免出现像现有全局平滑一样的光晕伪像过滤器。 WGIF用于增强单个图像的细节,去除单个图像的雾度以及融合不同曝光的图像。实验结果表明,所得算法产生的图像具有更好的视觉质量,同时,可以减少/避免光晕伪像出现在最终图像中,并且在运行时间上的增加可以忽略不计。

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