Novel Diffusion-Based Models for Image Restoration and Interpolation
Novel Diffusion-Based Models for Image Restoration and Interpolation.pdf
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© Springer International Publishing AG, part of Springer Nature 2019
The mathematical models based on partial differential equations (PDEs) have been increasingly applied in some traditionally engineering domains, such as signal and image processing, image analysis and computer vision, for more than three decades. Since the partial differential equations express continuous change, they have long been used to formulate dynamical phenomena in some important engineering areas.
These equations have been successfully used for solving many image processing and computer vision tasks in these years, leading to an entire new subdomain of this scientific field. Thus, they offer some important advantages to image processing and analysis and computer vision domains, such as their modelling flexibility, their strong mathematical foundation, and their numerical approximations representing reinterpretations of numerous classical image processing techniques.
