Open AccessBilateral filter acceleration based on weighted variable projection
Author(s) -
Yuan Mengke,
Zhang Xiaopeng
Publication year - 2018
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.2017.4592
Subject(s) - kernel (algebra) , acceleration , range (aeronautics) , computation , filter (signal processing) , bilateral filter , algorithm , projection (relational algebra) , computer science , constraint (computer aided design) , block (permutation group theory) , mathematical optimization , variable (mathematics) , function (biology) , mathematics , artificial intelligence , image (mathematics) , computer vision , engineering , mathematical analysis , physics , geometry , classical mechanics , combinatorics , evolutionary biology , biology , aerospace engineering
Due to the heavy computation cost, the bilateral filter cannot be applied to real‐time applications. To deal with this problem, many range kernel approximation based acceleration schemes have been proposed. However, all these methods use predefined basis function and assign the same penalisation for all range values to fulfil range kernel approximation. These constraints block from further improving the filtering accuracy and speed. Employing weighted variable projection, a new acceleration method which achieves state‐of‐the‐art performance is proposed. This is done by: (i) unleashing the constraint of using fixed basis function; (ii) exploiting the colour distribution information of the input image to perform a weighted approximation of the range kernel. Experiments demonstrate the superiority of the proposed method in gaining more accurate filtering results efficiently.