Guided Image Filtering
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AbstractIn 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.
All Author(s) ListHe KM, Sun J, Tang XO
Journal nameIEEE Transactions on Pattern Analysis and Machine Intelligence
Volume Number35
Issue Number6
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages1397 - 1409
LanguagesEnglish-United Kingdom
Keywordsbilateral filter; Edge-preserving filtering; linear time filtering
Web of Science Subject CategoriesComputer Science; Computer Science, Artificial Intelligence; COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE; Engineering; Engineering, Electrical & Electronic; ENGINEERING, ELECTRICAL & ELECTRONIC

Last updated on 2021-10-01 at 23:49