Edge-aware smoothing has proved to be a fundamental technique for various image processing and computer vision tasks. In this study, the authors introduce a local, non-iterative, and effective edge-preserving filter n...
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Edge-aware smoothing has proved to be a fundamental technique for various image processing and computer vision tasks. In this study, the authors introduce a local, non-iterative, and effective edge-preserving filter namely guided adaptive interpolation filter (GAIF). GAIF can be used as a post-processing step after any smoothing filter to improve its edge preservation performance without reformulation. GAIF has an O(N) computation complexity, where N is the total number of pixels in the image. To further increase the efficiency of GAIF at edge-preservation, two techniques are introduced and demonstrated. GAIF efficiency is demonstrated and compared to state-of-the-art techniques on a number of tasks including image smoothing, flash/no-flash image denoising/fusion, single image dehazing, and image details enhancement.
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