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Guided adaptive interpolation filter
Author(s) -
Waheed Waseem,
Alnasrawi Mukhalad,
Deng Guang
Publication year - 2020
Publication title -
iet image processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.401
H-Index - 45
eISSN - 1751-9667
pISSN - 1751-9659
DOI - 10.1049/iet-ipr.2019.1577
Subject(s) - smoothing , computer vision , computer science , edge preserving smoothing , artificial intelligence , filter (signal processing) , image processing , noise reduction , interpolation (computer graphics) , enhanced data rates for gsm evolution , non local means , image restoration , demosaicing , adaptive filter , bilateral filter , pixel , image (mathematics) , algorithm , color image
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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