Open AccessEfficient image sharpening and denoising using adaptive guided image filtering
Author(s) -
Pham Cuong Cao,
Jeon Jae Wook
Publication year - 2015
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.2013.0563
Subject(s) - sharpening , image denoising , noise reduction , artificial intelligence , computer science , image (mathematics) , computer vision , non local means , image processing , pattern recognition (psychology)
Enhancing the sharpness and reducing the noise of blurred, noisy images are crucial functions of image processing. Widely used unsharp masking filter‐based approaches suffer from halo‐artefacts and/or noise amplification, while noise‐ and halo‐free adaptive bilateral filtering (ABF) is computationally intractable. In this study, the authors present an efficient sharpening algorithm inspired by guided image filtering (GF). The author's proposed adaptive GF (AGF) integrates the shift‐variant technique, a part of ABF, into a guided filter to render crisp and sharpened outputs. Experiments showed the superiority of their proposed algorithm to existing algorithms. The proposed AGF sharply enhances edges and textures without causing halo‐artefacts or noise amplification, and it is efficiently implemented using a fast linear‐time algorithm.