Nicolas Passat, Phuc Ngo, Yukiko Kenmochi, Hugues Talbot
{"title":"Homotopic Affine Transformations in the 2D Cartesian Grid","authors":"Nicolas Passat, Phuc Ngo, Yukiko Kenmochi, Hugues Talbot","doi":"10.1007/s10851-022-01094-y","DOIUrl":null,"url":null,"abstract":"<p>Topology preservation is a property of affine transformations in <span>\\({{{\\mathbb {R}}}^2}\\)</span>, but not in <span>\\({{\\mathbb {Z}}}^2\\)</span>. In this article, given a binary object <span>\\({\\mathsf {X}} \\subset {{\\mathbb {Z}}}^2\\)</span> and an affine transformation <span>\\({{\\mathcal {A}}}\\)</span>, we propose a method for building a binary object <span>\\(\\widehat{{\\mathsf {X}}} \\subset {{\\mathbb {Z}}}^2\\)</span> resulting from the application of <span>\\({{\\mathcal {A}}}\\)</span> on <span>\\({\\mathsf {X}}\\)</span>. Our purpose is, in particular, to preserve the homotopy type between <span>\\({\\mathsf {X}}\\)</span> and <span>\\(\\widehat{{\\mathsf {X}}}\\)</span>. To this end, we formulate the construction of <span>\\(\\widehat{{\\mathsf {X}}}\\)</span> from <span>\\({{\\mathsf {X}}}\\)</span> as an optimization problem in the space of cellular complexes, and we solve this problem under topological constraints. More precisely, we define a cellular space <span>\\({{\\mathbb {H}}}\\)</span> by superimposition of two cellular spaces <span>\\({{\\mathbb {F}}}\\)</span> and <span>\\({{\\mathbb {G}}}\\)</span> corresponding to the canonical Cartesian grid of <span>\\({{\\mathbb {Z}}}^2\\)</span> where <span>\\({{\\mathsf {X}}}\\)</span> is defined, and a regular grid induced by the affine transformation <span>\\({{{\\mathcal {A}}}}\\)</span>, respectively. The object <span>\\(\\widehat{{\\mathsf {X}}}\\)</span> is then computed by building a homotopic transformation within the space <span>\\({{\\mathbb {H}}}\\)</span>, starting from the complex in <span>\\({{\\mathbb {G}}}\\)</span> resulting from the transformation of <span>\\({\\mathsf {X}}\\)</span> with respect to <span>\\({{\\mathcal {A}}}\\)</span> and ending at a complex fitting <span>\\(\\widehat{{\\mathsf {X}}}\\)</span> in <span>\\({{\\mathbb {F}}}\\)</span> that can be embedded back into <span>\\({{\\mathbb {Z}}}^2\\)</span>.</p>","PeriodicalId":16196,"journal":{"name":"Journal of Mathematical Imaging and Vision","volume":"64 1","pages":""},"PeriodicalIF":1.3000,"publicationDate":"2022-06-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Mathematical Imaging and Vision","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1007/s10851-022-01094-y","RegionNum":4,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 1
Abstract
Topology preservation is a property of affine transformations in \({{{\mathbb {R}}}^2}\), but not in \({{\mathbb {Z}}}^2\). In this article, given a binary object \({\mathsf {X}} \subset {{\mathbb {Z}}}^2\) and an affine transformation \({{\mathcal {A}}}\), we propose a method for building a binary object \(\widehat{{\mathsf {X}}} \subset {{\mathbb {Z}}}^2\) resulting from the application of \({{\mathcal {A}}}\) on \({\mathsf {X}}\). Our purpose is, in particular, to preserve the homotopy type between \({\mathsf {X}}\) and \(\widehat{{\mathsf {X}}}\). To this end, we formulate the construction of \(\widehat{{\mathsf {X}}}\) from \({{\mathsf {X}}}\) as an optimization problem in the space of cellular complexes, and we solve this problem under topological constraints. More precisely, we define a cellular space \({{\mathbb {H}}}\) by superimposition of two cellular spaces \({{\mathbb {F}}}\) and \({{\mathbb {G}}}\) corresponding to the canonical Cartesian grid of \({{\mathbb {Z}}}^2\) where \({{\mathsf {X}}}\) is defined, and a regular grid induced by the affine transformation \({{{\mathcal {A}}}}\), respectively. The object \(\widehat{{\mathsf {X}}}\) is then computed by building a homotopic transformation within the space \({{\mathbb {H}}}\), starting from the complex in \({{\mathbb {G}}}\) resulting from the transformation of \({\mathsf {X}}\) with respect to \({{\mathcal {A}}}\) and ending at a complex fitting \(\widehat{{\mathsf {X}}}\) in \({{\mathbb {F}}}\) that can be embedded back into \({{\mathbb {Z}}}^2\).
期刊介绍:
The Journal of Mathematical Imaging and Vision is a technical journal publishing important new developments in mathematical imaging. The journal publishes research articles, invited papers, and expository articles.
Current developments in new image processing hardware, the advent of multisensor data fusion, and rapid advances in vision research have led to an explosive growth in the interdisciplinary field of imaging science. This growth has resulted in the development of highly sophisticated mathematical models and theories. The journal emphasizes the role of mathematics as a rigorous basis for imaging science. This provides a sound alternative to present journals in this area. Contributions are judged on the basis of mathematical content. Articles may be physically speculative but need to be mathematically sound. Emphasis is placed on innovative or established mathematical techniques applied to vision and imaging problems in a novel way, as well as new developments and problems in mathematics arising from these applications.
The scope of the journal includes:
computational models of vision; imaging algebra and mathematical morphology
mathematical methods in reconstruction, compactification, and coding
filter theory
probabilistic, statistical, geometric, topological, and fractal techniques and models in imaging science
inverse optics
wave theory.
Specific application areas of interest include, but are not limited to:
all aspects of image formation and representation
medical, biological, industrial, geophysical, astronomical and military imaging
image analysis and image understanding
parallel and distributed computing
computer vision architecture design.