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Fast Gauss Bilateral Filtering
Author(s) -
Yoshizawa Shin,
Belyaev Alexander,
Yokota Hideo
Publication year - 2010
Publication title -
computer graphics forum
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.578
H-Index - 120
eISSN - 1467-8659
pISSN - 0167-7055
DOI - 10.1111/j.1467-8659.2009.01544.x
Subject(s) - tone mapping , computer science , bilateral filter , filter (signal processing) , computational complexity theory , convolution (computer science) , algorithm , dimension (graph theory) , gaussian filter , gauss , range (aeronautics) , gaussian process , noise reduction , computer vision , image (mathematics) , gaussian , artificial intelligence , high dynamic range , mathematics , dynamic range , materials science , composite material , artificial neural network , physics , quantum mechanics , pure mathematics
In spite of high computational complexity, the bilateral filter and its modifications and extensions have recently become very popular image and shape processing tools. In this paper, we propose a fast and accurate approximation of the bilateral filter. Our approach combines a dimension elevation trick with a Fast Gauss Transform. First we represent the bilateral filter as a convolution in a high dimensional space. Then the convolution is efficiently approximated by using space partitioning and Gaussian function expansions. Advantages of our approach include linear computational complexity, user‐specified precision, and an ability to process high dimensional and non‐uniformly sampled data. We demonstrate capabilities of the approach by considering its applications to the image and volume denoising and high‐dynamic‐range tone mapping problems.