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Main Authors: Kahra, Marvin, Breuß, Michael, Kleefeld, Andreas, Welk, Martin
Format: Preprint
Published: 2024
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Online Access:https://arxiv.org/abs/2411.10141
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author Kahra, Marvin
Breuß, Michael
Kleefeld, Andreas
Welk, Martin
author_facet Kahra, Marvin
Breuß, Michael
Kleefeld, Andreas
Welk, Martin
contents Mathematical morphology is a part of image processing that uses a window that moves across the image to change certain pixels according to certain operations. The concepts of supremum and infimum play a crucial role here, but it proves challenging to define them generally for higher-dimensional data, such as colour representations. Numerous approaches have therefore been taken to solve this problem with certain compromises. In this paper we will analyse the construction of a new approach, which we have already presented experimentally in paper [Kahra, M., Breuß, M., Kleefeld, A., Welk, M., DGMM 2024, pp. 325-337]. This is based on a method by Burgeth and Kleefeld [Burgeth, B., Kleefeld, A., ISMM 2013, pp. 243-254], who regard the colours as symmetric $2\times2$ matrices and compare them by means of the Loewner order in a bi-cone through different suprema. However, we will replace the supremum with the LogExp approximation for the maximum instead. This allows us to transfer the associativity of the dilation from the one-dimensional case to the higher-dimensional case. In addition, we will investigate the minimality property and specify a relaxation to ensure that our approach is continuously dependent on the input data.
format Preprint
id arxiv_https___arxiv_org_abs_2411_10141
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Matrix-Valued LogSumExp Approximation for Colour Morphology
Kahra, Marvin
Breuß, Michael
Kleefeld, Andreas
Welk, Martin
Computer Vision and Pattern Recognition
68R01
Mathematical morphology is a part of image processing that uses a window that moves across the image to change certain pixels according to certain operations. The concepts of supremum and infimum play a crucial role here, but it proves challenging to define them generally for higher-dimensional data, such as colour representations. Numerous approaches have therefore been taken to solve this problem with certain compromises. In this paper we will analyse the construction of a new approach, which we have already presented experimentally in paper [Kahra, M., Breuß, M., Kleefeld, A., Welk, M., DGMM 2024, pp. 325-337]. This is based on a method by Burgeth and Kleefeld [Burgeth, B., Kleefeld, A., ISMM 2013, pp. 243-254], who regard the colours as symmetric $2\times2$ matrices and compare them by means of the Loewner order in a bi-cone through different suprema. However, we will replace the supremum with the LogExp approximation for the maximum instead. This allows us to transfer the associativity of the dilation from the one-dimensional case to the higher-dimensional case. In addition, we will investigate the minimality property and specify a relaxation to ensure that our approach is continuously dependent on the input data.
title Matrix-Valued LogSumExp Approximation for Colour Morphology
topic Computer Vision and Pattern Recognition
68R01
url https://arxiv.org/abs/2411.10141