Guided Image Filtering
Guided Image Filtering
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DOI：
10.1007/978-3-642-15549-9_1
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发表时间：
2010-09
影响因子：
23.6
通讯作者：
Kaiming He;Jian Sun-;Xiaoou Tang
中科院分区：
文献类型：
--
作者：
Kaiming He;Jian Sun-;Xiaoou Tang
在本文中，我们提出了一种新的显式图像滤波器称为引导滤波器。从局部线性模型导出，引导滤波器通过考虑引导图像的内容来计算滤波输出，所述引导图像可以是输入图像本身或另一不同图像。引导滤波器可以像流行的双边滤波器[1]一样用作边缘保持平滑算子，但它在边缘附近具有更好的行为。引导滤波器也是一个比平滑更通用的概念：它可以将引导图像的结构转移到滤波输出，从而实现新的滤波应用，如去雾和引导羽化。此外，引导滤波器自然具有快速和非近似线性时间算法，而不管核大小和强度范围。目前，它是最快的边缘保持过滤器之一。实验结果表明，该滤波器在边缘平滑、细节增强、HDR压缩、图像抠像/羽化、去雾、联合上采样等多种计算机视觉和计算机图形应用中具有良好的效果。
In this paper, we propose a novel explicit image filter called guided filter. Derived from a local linear model, the guided filter computes the filtering output by considering the content of a guidance image, which can be the input image itself or another different image. The guided filter can be used as an edge-preserving smoothing operator like the popular bilateral filter [1], but it has better behaviors near edges. The guided filter is also a more generic concept beyond smoothing: It can transfer the structures of the guidance image to the filtering output, enabling new filtering applications like dehazing and guided feathering. Moreover, the guided filter naturally has a fast and nonapproximate linear time algorithm, regardless of the kernel size and the intensity range. Currently, it is one of the fastest edge-preserving filters. Experiments show that the guided filter is both effective and efficient in a great variety of computer vision and computer graphics applications, including edge-aware smoothing, detail enhancement, HDR compression, image matting/feathering, dehazing, joint upsampling, etc.