The mathematical characteristic of the fifth order Laplace contour filters used in digital image processing

The Laplace operator is a differential operator which is used to detect edges of objects in digital images. This paper presents the properties of the most commonly used fifth-order pixels Laplace filters including the difference schemes used to derive them (finite difference method – FDM and finite...

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Bibliographic Details
Main Authors: Ireneusz Winnicki, Slawomir Pietrek, Janusz Jasinski, Krzysztof Kroszczynski
Format: Article
Language:English
Published: Polish Academy of Sciences 2022-10-01
Series:Advances in Geodesy and Geoinformation
Subjects:
Online Access:https://journals.pan.pl/Content/124842/PDF/e26_int.pdf
Description
Summary:The Laplace operator is a differential operator which is used to detect edges of objects in digital images. This paper presents the properties of the most commonly used fifth-order pixels Laplace filters including the difference schemes used to derive them (finite difference method – FDM and finite element method – FEM). The results of the research concerning third-order pixels matrices of the convolution Laplace filters used for digital processing of images were presented in our previous paper: The mathematical characteristic of the Laplace contour filters used in digital image processing. The third order filters is presented byWinnicki et al. (2022). As previously, the authors focused on the mathematical properties of the Laplace filters: their transfer functions and modified differential equations (MDE). The relations between the transfer function for the differential Laplace operator and its difference operators are described and presented here in graphical form. The impact of the corner elements of the masks on the results is also discussed. A transfer function, is a function characterizing properties of the difference schemes applied to approximate differential operators. Since they are relations derived in both types of spaces (continuous and discrete), comparing them facilitates the assessment of the applied approximation method.
ISSN:2720-7242