000			02813nam a22004095i 4500
710	2		_aSpringerLink (Online service) _9106996
999			_c111219 _d111219
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003			ES-MaUEC
005			20230102113501.0
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008			180702s2019 gw a o |||| 0|eng d
020			_a9783319930060
024	7		_a10.1007/978-3-319-93006-0 _2doi
040			_bspa _dES-MaUEC _cES-MaUEC
050		4	_aTA1637 _b2019 EB
100	1		_aBarbu, Tudor _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9673213
245	1	0	_aNovel Diffusion-Based Models for Image Restoration and Interpolation _cby Tudor Barbu.
264		1	_aCham _bSpringer International Publishing : _bImprint: Springer _c2019.
300			_a1 recurso en línea (VIII, 126 páginas) _b31 ilustraciones, 8 ilustraciones a color
336			_2rdacontent _aTexto _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
347			_atext file _bPDF
490	0		_aEngineering (Springer-11647)
490	0		_aSignals and Communication Technology _x1860-4862
505	0		_aIntroduction -- Linear PDE-based Image Denoising Schemes -- Nonlinear Diffusion-based Image Restoration Models -- Variational and PDE Models for Image Interpolation -- Conclusions.
520	3		_aThis book covers two essential PDE-based image processing fields: image denoising and image inpainting. It describes the state-of-the-art PDE-based image restoration and interpolation (inpainting) techniques, focusing on the latest advances in PDE-based image processing and analysis, and explores novel techniques involving diffusion-based models and variational schemes. The PDE and variational schemes clearly outperform the conventional approaches in these areas, and can successfully remove image noise and reconstruct missing or highly degraded regions, while preserving the essential features and avoiding unintended effects. The book addresses researchers and graduate students, but is also well suited for professionals in both the mathematics and electrical engineering domains, as it provides rigorous mathematical investigations of the image processing models described, as well as mathematical treatments for the numerical approximation schemes of these differential models. .
988			_aPrimersemestre_2019_Engineering
650		7	_2embne _9669495 _aProceso de imágenes
776	0	8	_iPrinted edition: _z9783030065669
776	0	8	_iPrinted edition: _z9783319930053
776	0	8	_iPrinted edition: _z9783319930077
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-319-93006-0 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_dz _feng _ggw _h0 _b04/2020 _eIG _zSI