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Introduction to variational image-processing models and applications.

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Název: Introduction to variational image-processing models and applications.
Autoři: Chen, Ke
Zdroj: International Journal of Computer Mathematics; Jan2013, Vol. 90 Issue 1, p1-8, 8p
Témata: IMAGE processing, MATHEMATICAL models, APPLICATION software, IMAGE quality in imaging systems, PARTIAL differential equations, IMAGE segmentation, IMAGE reconstruction
Abstrakt: Variational image-processing models offer high-quality processing capabilities for imaging. They have been widely developed and used in the last two decades, enriching the fields of mathematics as well as information science. Mathematically, several tools are needed: energy optimization, regularization, partial differential equations, level set functions, and numerical algorithms. This special issue presents readers with nine excellent research papers covering topics from research work intovariational image-processing models, algorithms and applications, including image denoising, image deblurring, image segmentation, image reconstruction, restoration of mixed noise types and three-dimensional surface restoration. [ABSTRACT FROM PUBLISHER]
Copyright of International Journal of Computer Mathematics is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Databáze: Complementary Index
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  Data: Introduction to variational image-processing models and applications.
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  Data: <searchLink fieldCode="AR" term="%22Chen%2C+Ke%22">Chen, Ke</searchLink>
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  Data: International Journal of Computer Mathematics; Jan2013, Vol. 90 Issue 1, p1-8, 8p
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  Data: <searchLink fieldCode="DE" term="%22IMAGE+processing%22">IMAGE processing</searchLink><br /><searchLink fieldCode="DE" term="%22MATHEMATICAL+models%22">MATHEMATICAL models</searchLink><br /><searchLink fieldCode="DE" term="%22APPLICATION+software%22">APPLICATION software</searchLink><br /><searchLink fieldCode="DE" term="%22IMAGE+quality+in+imaging+systems%22">IMAGE quality in imaging systems</searchLink><br /><searchLink fieldCode="DE" term="%22PARTIAL+differential+equations%22">PARTIAL differential equations</searchLink><br /><searchLink fieldCode="DE" term="%22IMAGE+segmentation%22">IMAGE segmentation</searchLink><br /><searchLink fieldCode="DE" term="%22IMAGE+reconstruction%22">IMAGE reconstruction</searchLink>
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  Data: Variational image-processing models offer high-quality processing capabilities for imaging. They have been widely developed and used in the last two decades, enriching the fields of mathematics as well as information science. Mathematically, several tools are needed: energy optimization, regularization, partial differential equations, level set functions, and numerical algorithms. This special issue presents readers with nine excellent research papers covering topics from research work intovariational image-processing models, algorithms and applications, including image denoising, image deblurring, image segmentation, image reconstruction, restoration of mixed noise types and three-dimensional surface restoration. [ABSTRACT FROM PUBLISHER]
– Name: Abstract
  Label:
  Group: Ab
  Data: <i>Copyright of International Journal of Computer Mathematics is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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