New anisotropic diffusion operator in images filtering
dc.contributor.author | Vera, M | |
dc.contributor.author | Gonzalez, E | |
dc.contributor.author | Huérfano, Y | |
dc.contributor.author | Gelvez, E | |
dc.contributor.author | Valbuena, O | |
dc.date.accessioned | 2020-04-16T21:50:59Z | |
dc.date.available | 2020-04-16T21:50:59Z | |
dc.date.issued | 2020 | |
dc.description.abstract | The anisotropic di usion lters have become in the fundamental bases to address the medical images noise problem. The main attributes of these lters are: the noise removal e ectiveness and the preservation of the information belonging to the edges that delimit the objects of an image. Due to these excellent attributes, through this article, a comparative study is proposed between a new di usion operator and the Lorentz operator, proposed by the pioneers of anisotropic di usion. For this, a strategy consisting of two phases is designed. In the rst, called operator construction, the composition of functions is used to generate a new di usion operator that meets with the conditions reported for this kind of the mathematical object. In the second phase, denominated ltering, a synthetic cardiac images database, based on computed tomography, is ltered using the aforementioned operators. According with the value obtained for the peak of the signal-to-noise ratio, the new operator shows similar performance to the Lorentz operator. The implementation of this new operator contributes to the generation of new knowledge in digital image processing context. | eng |
dc.format.mimetype | eng | |
dc.identifier.doi | https://doi.org/10.1088/1742-6596/1448/1/012019 | |
dc.identifier.issn | 17426596 | |
dc.identifier.uri | https://hdl.handle.net/20.500.12442/5118 | |
dc.language.iso | eng | eng |
dc.publisher | IOP Publishing | eng |
dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | eng |
dc.rights.accessrights | info:eu-repo/semantics/openAccess | eng |
dc.rights.uri | http://creativecommons.org/licenses/by-nc-nd/4.0/ | |
dc.source | Journal of Physics: Conference Series | eng |
dc.source | Vol. 1448 (2020) | eng |
dc.title | New anisotropic diffusion operator in images filtering | eng |
dc.type | article | eng |
dc.type.driver | article | eng |
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oaire.version | info:eu-repo/semantics/publishedVersion | eng |