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Record Nr. |
UNINA9910337465203321 |
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Autore |
Barbu Tudor |
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Titolo |
Novel Diffusion-Based Models for Image Restoration and Interpolation / / by Tudor Barbu |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2019 |
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ISBN |
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Edizione |
[1st ed. 2019.] |
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Descrizione fisica |
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1 online resource (VIII, 126 p. 31 illus., 8 illus. in color.) |
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Collana |
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Signals and Communication Technology, , 1860-4862 |
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Disciplina |
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Soggetti |
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Optical data processing |
Partial differential equations |
Computational intelligence |
Image Processing and Computer Vision |
Partial Differential Equations |
Computational Intelligence |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Introduction -- Linear PDE-based Image Denoising Schemes -- Nonlinear Diffusion-based Image Restoration Models -- Variational and PDE Models for Image Interpolation -- Conclusions. |
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Sommario/riassunto |
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This 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 |
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image processing models described, as well as mathematical treatments for the numerical approximation schemes of these differential models. . |
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