This project addresses the area of image and video inpainting, the technique of modifying an image in an undetectable form. The goals and applications of inpainting, which is as ancient as art itself, are numerous, from the restoration of damaged paintings and photographs to the removal of selected objects in a scene and the discovery of data behind occlusions. Image inpainting is also important for less-conventional applications such as wireless transmission and compression and image integration from camera arrays. The goal of this project is to develop a working solution to image, video, three dimensional, and multiple views inpainting and to address applications such as image and film restoration and alteration, image recovery from camera arrays, and filling-in of holes in 3D range data. Biological aspects of inpainting, through its fascinating possible connections with camouflage and the filling-in of the human blind spot, are investigated as well. The theory and applications of this project cover very diverse areas such as image processing, partial differential equations and fluid dynamics, numerical analysis, art, computer graphics, entertainment, and biology.
The inpainting problem is addressed as the computation of a smooth continuation of the available spatial and temporal information surrounding the region to be filled-in. This is achieved via partial differential equations, which incorporate principles ranging from fluid dynamics to Gestalt's smooth boundary continuation. The combination of these techniques with more classical texture synthesis algorithms is also addressed and exploited in this project. The research addresses the problem in its generality, assuming diverse and large regions to be inpainted, and derives both fundamental theoretical aspects and practical working systems.
