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Visualitza Departament de Tecnologies de la Informació i les Comunicacions per matèria "Image denoising"

Visualitza Departament de Tecnologies de la Informació i les Comunicacions per matèria "Image denoising"

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  • Ghimpeteanu, Gabriela; Batard, Thomas; Bertalmío, Marcelo; Levine, Stacey (Institute of Electrical and Electronics Engineers (IEEE), 2016)
    In this paper, we consider an image decomposition model that provides a novel framework for image denoising. The model computes the components of the image to be processed in a moving frame that encodes its local geometry ...
  • Fedorov, Vadim; Ballester, Coloma (Institute of Electrical and Electronics Engineers (IEEE), 2017)
    This work presents an extension of the Non-Local Means denoising method, that effectively exploits the affine invariant self-similarities present in images of real scenes. Our method provides a better image denoising result ...
  • Ghimpeteanu, Gabriela; Batard, Thomas; Bertalmío, Marcelo; Levine, Stacey (Springer, 2014)
    In this paper, we provide a new non-local method for image denoising. The key idea we develop is to denoise the components of the image in a well-chosen moving frame instead of the image itself.We prove the relevance of ...
  • Bertalmío, Marcelo; Levine, Stacey (SIAM (Society for Industrial and Applied Mathematics), 2014)
    In this article we argue that when an image is corrupted by additive noise, its curvature image is less affected by it, i.e. the PSNR of the curvature image is larger. We speculate that, given a denoising method, we may ...
  • Ghimpeteanu, Gabriela; Kane, David; Batard, Thomas; Levine, Stacey; Bertalmío, Marcelo (Institute of Electrical and Electronics Engineers (IEEE), 2016)
    We propose a fast, local denoising method where the Euclidean curvature of the noisy image is approximated in a regularizing manner and a clean image is reconstructed from this smoothed curvature. User preference tests ...

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