Open AccessAccelerate bilateral filter using Hermite polynomials
Author(s) -
Dai Longquan,
Yuan Mengke,
Zhang Xiaopeng
Publication year - 2014
Publication title -
electronics letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.375
H-Index - 146
eISSN - 1350-911X
pISSN - 0013-5194
DOI - 10.1049/el.2014.2758
Subject(s) - bilateral filter , filter (signal processing) , hermite polynomials , pixel , kernel (algebra) , algorithm , mathematics , kernel adaptive filter , computational complexity theory , range (aeronautics) , noise (video) , image processing , nonlinear system , dynamic range , noise reduction , image (mathematics) , cubic hermite spline , computer science , artificial intelligence , filter design , computer vision , discrete mathematics , mathematical analysis , polynomial , physics , engineering , quantum mechanics , nearest neighbor interpolation , linear interpolation , aerospace engineering
The bilateral filter (BF) as an edge‐preserving lowpass filter is a valuable tool in various image processing tasks, including noise reduction and dynamic range compression. However, its computational cost is too high to apply in the real‐time processing tasks as the range kernel, which acts on the pixel intensities, making the averaging process nonlinear and computationally intensive, particularly when the spatial filter is large. Using the well‐known Hermite polynomials, a BF accelerating method is proposed, which reduces the computational complexity from O ( r 2 n ) to O ( n ), where r denotes the filter size of a BF and n is the total number of pixels in an image.