Open AccessFast bilateral filtering
Author(s) -
Zhang Xueli,
Dai Longquan
Publication year - 2019
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
ISSN - 1350-911X
DOI - 10.1049/el.2018.7278
Subject(s) - computational complexity theory , kernel (algebra) , bilateral filter , smoothing , convolution (computer science) , algorithm , filter (signal processing) , exponential function , range (aeronautics) , computer science , edge preserving smoothing , artificial intelligence , computer vision , exponential smoothing , mathematics , image (mathematics) , engineering , mathematical analysis , combinatorics , artificial neural network , aerospace engineering
The bilateral filter is a fundamental smoothing tool in image processing and computer vision due to its outstanding edge‐preserving ability. However, the computational complexity depends on the size of the support of the spatial kernel. This drawback makes bilateral filtering time‐consuming and significantly limits its applications. A novel strategy to turn the range kernel of the bilateral filter into a sum of exponential functions is proposed. As the convolution with the exponential function can be accelerated by the O ( 1 ) box filtering, the computational complexity of the bilateral thus becomes O ( 1 ) . Experimental results disclose that the proposed algorithm is competitive with the state‐of‐the‐art algorithms in terms of filtering accuracy and computational efficiency.