Predictable blur behaviour for the bilateral filter

Researching a method for linear behaviour between the blurriness and spatial filter size of the bilateral filter

Bachelor Thesis (2024)
Author(s)

B.P. Snelten (TU Delft - Electrical Engineering, Mathematics and Computer Science)

Contributor(s)

E Eisemann – Mentor (TU Delft - Computer Graphics and Visualisation)

M.L. Molenaar – Mentor (TU Delft - Computer Graphics and Visualisation)

J. Sun – Graduation committee member (TU Delft - Pattern Recognition and Bioinformatics)

Faculty
Electrical Engineering, Mathematics and Computer Science
More Info
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Publication Year
2024
Language
English
Graduation Date
28-06-2024
Awarding Institution
Delft University of Technology
Project
['CSE3000 Research Project']
Programme
['Computer Science and Engineering']
Faculty
Electrical Engineering, Mathematics and Computer Science
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Abstract

Unlike traditional blur filters, the bilateral filter exhibits non-linear blur behaviour as its kernel size increases. This atypical blur behaviour makes it challenging to find a good σr . This paper investigates the underlying reasons for this behaviour and proposes methods to align the bilateral filter’s blur scaling linearly with its spatial filter size. Using local frequency analyses to quantify blur levels, we introduce an approach that finds the best σr through iterative search. Results demonstrate that the pro- posed method effectively counters the atypical blur behaviour. However, the proposed method does not perform sufficiently when handling very large kernel sizes. The proposed method can be used to abstract away the σr parameter when seeking linear blur behaviour in the bilateral filter. Further re- search is needed to make it functional for very large kernel sizes.

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