Preface:
This following list of works (by others) have been kindly provided to us
either directly by their authors or indirectly through other sources, each of
which has cited at least one of our following earlier works on image inpainting (data
by April 2004):
· T. F. Chan and J. Shen, “Mathematical models for local non-texture inpainting,” SIAM J. Appl. Math., 62(3), 1019-1043, 2001.
· T. F. Chan and J. Shen, “Non-texture inpainting by curvature-driven diffusions (CDD),” J. Visual Comm. Image Rep., 12(4), 436-449, 2001.
· T. F. Chan, S.-H. Kang, and J. Shen, “Euler’s elastica and curvature-based image inpainting,” SIAM J. Appl. Math., 63(2), 564-592, 2002.
· S. Esedoglu and J. Shen, “Digital inpainting based on the Mumford-Shah-Euler image model,” Europ. J. Appl. Math., 13, 353-370, 2002.
· J. Shen, “Inpainting and the fundamental problem of image processing,” SIAM News, 36(5), 2003.
Decent mathematical models, though without legs, certainly possess the
holy wings that can take them far beyond one could possibly imagine. (Please
contact the corresponding authors for more information.) Here they are: from A to Z …
1. Levin, Zomet, and Weiss, “Learning how to inpaint from global image statistics,” The Hebrew Univ. Jerusalem, Israel. inpaintingA.pdf.
2. Shih, Lu, and Chang, “An automatic image inpaint tool,” Tamkang Univ, Taiwan, inpaintingB.pdf .
3. Savchenko, Kejekine, and Unno, “A practical image retouching method,” Hosei Univ./Tokyo Institute of Tech. Japan, inpaintingC.pdf.
4.
Grossauer and Scherzer, “Using the
complex Ginzburg-Landau equation for digital inapinting,” Univ. Innsbruck,
Austria. inpaintingD.pdf.
5. Kojekine and Saychenko, “Using CSRBFS for surface retouching,” Tokyo Inst. Tech/Hosei Univ., Japan, inpaintingE.pdf.
6.
Verdera, Caselles, Bertalmio, and Sapiro,
“Inpianting surface holes,” University of Minnesota, USA, inpaintingF.pdf
7. Greer and Bertozzi, “H1 solutions to a class of 4th order nonlinear equations for image processing,” UCLA, USA, inpaintingG.pdf
8. Reres, Reinders, and Biemond, “Image sequence restoration in the presence of pathological motion and severe artifacts,” Delft Univ.Tech., Netherlands, inpaintingH.pdf.
9. Rares, Reinders, Biemond, and Lagendijk, “A spatiotemporal image sequence restoration algorithm,” Delft Univ.Tech., Netherlands, inpaintingI.pdf.
10. Bertalmio, Bertozzi, and Sapiro, “Navier-Stokes, fluid dynamics, and image and video inpainting,” Spain/UCLA/Univ. Minnesota, inpaintingJ.pdf.
11. Kojekine, Savchenko, Senin, and Hagiwara, “An approach to surface retouching and mesh smoothing,” Japan/Russia, inpaintingK.pdf.
12. Jia and Tang, “Image repairing: robust image synthesis by adaptive nd tensor voting,” Hong Kong, inpaintingL.pdf.
13. Tsai and Osher, “Level set methods and their applications in image science,” Princeton/UCLA, inpaintingM.pdf.
14. Ballester, Bertalmio, Caselles, Sapiro, “A variational model for filling-in,” France/Spain/Univ Minnesota, inpaintingN.pdf.
15. Oliveira, Bowen, Mckenna, and Chang, “Fast digital image inpainting,”, Sunny Stony Brook, NY, inpaintingO.pdf.
16. Cant and Langensiepen, “A multiscale method for automated inpainting,” Nottingham Trent University, inpaintingP.pdf.
17. Demanet, Song, and Chan, “Image inpainting by corresponding maps: a deterministic approach,” Caltech/UCLA, inpaintingQ.pdf.
18. Ballester, Bertalmio, Caselles, Sapiro, and Verdera, “Filling-in by joint interpolation of vector fields and gray levels,” Spain/USA, inpaintingR.pdf.
19. Criminisi and Toyama, “Object Removal by Exemplar-Based Inpainting,” Microsoft at UK & USA, inpaintingS.pdf.
20. Haber and Tenorio, “Learning regularization functions – a supervised training approach,” Emory/Atlanta and Colorado, inpaintingT.pdf.
21. Kim, Lin, Hong, and Shum, “Variational specular separation using color and polarization,” Microsoft Asia, inpaintingU.pdf.
22. Tsai, Yezzi, and Willsky, “Curve evolution implementation of the Mumford-Shah functional for image segmentation, denoising, interpolation, and magnification,” Georgia Inst. Tech. and MIT, inpaintingV.pdf.
23. Ballester, Caselles, and Verdera, “Disocclusion by joint interpolation of vector fields and gray levels,” Barcelona, Spain, inpaintingW.pdf.
24. Guo, Zhu, and Wu, “A mathematical theory of primal sketch and sketchability,” Vision/Statistics@UCLA, inpaintingX.pdf.
25. Mio, Srivastava and Liu, “Learning and Bayesian shape extraction for object recognition,” Florida State Univ., inpaintingY.pdf.
26. Bertozzi and Greer, “Low-curvature image simplifiers: Global regularity of smooth solutions and Laplacian limiting schemes,” UCLA/Duke, inpaintingZ.pdf. (Comm. Pure. Appl. Math.).
Last upated: April, 2004.