MATLAB-Python-inpainting-codes
Partial differential equation methods for image inpainting. This book is concerned with digital image processing techniques that use partial differential equations (PDEs) for the task of image `inpainting’, an artistic term for virtual image restoration or interpolation, whereby missing or occluded parts in images are completed based on information provided by intact parts. Computer graphic designers, artists and photographers have long used manual inpainting to restore damaged paintings or manipulate photographs. Today, mathematicians apply powerful methods based on PDEs to automate this task. This book introduces the mathematical concept of PDEs for virtual image restoration. It gives the full picture, from the first modelling steps originating in Gestalt theory and arts restoration to the analysis of resulting PDE models, numerical realisation and real-world application. This broad approach also gives insight into functional analysis, variational calculus, optimisation and numerical analysis and will appeal to researchers and graduate students in mathematics with an interest in image processing and mathematical analysis.
Keywords for this software
References in zbMATH (referenced in 9 articles , 1 standard article )
Showing results 1 to 9 of 9.
Sorted by year (- Breuß, Michael; Hoeltgen, Laurent; Radow, Georg: Towards PDE-based video compression with optimal masks prolongated by optic flow (2021)
- Welk, Martin; Weickert, Joachim: PDE evolutions for M-smoothers in one, two, and three dimensions (2021)
- Zhang, Min; Zhang, Guo-Feng: Fast image inpainting strategy based on the space-fractional modified Cahn-Hilliard equations (2021)
- Brkić, Antun Lovro; Novak, Andrej: A nonlocal image inpainting problem using the linear Allen-Cahn equation (2020)
- Hocking, L. Robert; Holding, Thomas; Schönlieb, Carola-Bibiane: Analysis of artifacts in shell-based image inpainting: why they occur and how to eliminate them (2020)
- Andrisani, Andrea; Mininni, Rosa Maria; Mazzia, Francesca; Settanni, Giuseppina; Iurino, Alessandro; Tangaro, Sabina; Tateo, Andrea; Bellotti, Roberto: Applications of PDEs inpainting to magnetic particle imaging and corneal topography (2019)
- Hoeltgen, Laurent; Kleefeld, Andreas; Harris, Isaac; Breuss, Michael: Theoretical foundation of the weighted Laplace inpainting problem. (2019)
- Galerne, Bruno; Leclaire, Arthur: Texture inpainting using efficient Gaussian conditional simulation (2017)
- Schönlieb, Carola-Bibiane: Partial differential equation methods for image inpainting (2015)