![]() ![]() Verdera, "Filling-in by joint interpolation of vector fields and grey levels," University of Minnesota IMA TR, April 2000. Shen, "Mathematical models for local deter-ministic inpaintings," UCLA CAM TR 00-11, March 2000. Turk, "LCIS: A boundary hierarchy for detail-preserving contrast reduction," Computer Graphics, pp. Bertozzi The mathematics of moving contact lines in thin liquid films. Osher, "A varia-tional level-set approach to multiphase motion," J. Osher, personal communication, October 1999. Nonlinear total variation based noise removal algorithms. Explicit algorithms for a new time dependent model based on level set motion for nonlinear de-bluring and noise removal. Journal of Computational Physics, 79:12-49, 1988. Fronts propagating with curvature dependent speed: algorithms based on Hamilton-Jacobi for-mulations. Image selective smoothing and edge detection by nonlinear. Malik Scale-space and edge detection using anisotropic diffusion. University of California Santa Barbara Preprint, 1999. A new image processing primitive: reconstructing images from modified flow fields. Shiota, Filtering, Segmen-tation, and Depth, Springer-Verlag, Berlin, 1993. ![]() Texture characterization via joint statistics of wavelet coefficient magnitudes. Pyramid based texture analy-sis/ synthesis. IEEE International Conference Computer Vi-sion, pp. Leung, "Texture synthesis by non-parametric sampling," Proc. Combining Frequency and spatial domain information for fast interactive image noise removal. Interpolation of missing data in image sequences. Detection of missing data in image sequences. The Restorer's Handbook of Easel Painting. Applications of this technique include the restoration of old photographs and damaged film removal of superimposed text like dates, subtitles, or publicity and the removal of entire objects from the image like microphones or wires in special effects. In addition, no limitations are imposed on the topology of the region to be inpainted. ![]() This is automatically done (and in a fast way), thereby allowing to simultaneously fill-in numerous regions containing completely different structures and surrounding backgrounds. In contrast with previous approaches, the technique here introduced does not require the user to specify where the novel information comes from. The fill-in is done in such a way that isophote lines arriving at the regions' boundaries are completed inside. After the user selects the regions to be restored, the algorithm automatically fills-in these regions with information surrounding them. PHOTO INPAINT PROFESSIONALIn this paper, we introduce a novel algorithm for digital inpainting of still images that attempts to replicate the basic techniques used by professional restorators. The goals and applications of inpainting are numerous, from the restoration of damaged paintings and photographs to the removal/replacement of selected objects. Inpainting, the technique of modifying an image in an undetectable form, is as ancient as art itself. ![]()
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