title: Guided image filtering.
abstract: 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.
authors.affiliation: Visual Computing Group, Microsoft Research Asia, Microsoft Building 2, #5 Dan Leng Street, Hai Dian District, Beijing 100080, China. kahe@microsoft.com
authors.forename: Kaiming
authors.initials: K
authors.lastname: He
authors.forename: Jian
authors.initials: J
authors.lastname: Sun
authors.forename: Xiaoou
authors.initials: X
authors.lastname: Tang