Geometric-variational approach for color image enhancement and segmentation

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 1682, Issue , 1999, Pages 294-305

  Kimmel, Ron ^a   Sochen, Nir A ^a  

^a TECHNION ISRAEL INSTITUTE OF TECHNOLOGY   (Israel)

Author keywords

[No Author keywords available]

Indexed keywords

COLOR; COMPUTER VISION; GRADIENT METHODS; IMAGE ENHANCEMENT; IMAGE SEGMENTATION;

BELTRAMI FRAMEWORK; COLOR IMAGE ENHANCEMENT; GAMMA CONVERGENCE; GRADIENT DESCENT METHOD; HIGHER DIMENSIONS; MUMFORD-SHAH FUNCTIONALS; SEGMENTATION ALGORITHMS; VARIATIONAL APPROACHES;

COLOR IMAGE PROCESSING;

EID: 84948188087     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/3-540-48236-9_26     Document Type: Conference Paper

References (24)

1. L. Ambrosio and V. M. Tortorelli, “Approximation of functionals depending on jumps by elliptic functionals via Γ-convergence", Comm. Pure Appl. Math., 43 (1990), 999-1036.
2. L. Ambrosio and V. M. Tortorelli, “On the approximation of free discontinuity problems", Boll. Un. Mat. It., 7 (1992), 105-123.
3. E. Di Giorgi, M. Carriero, and A. Leaci, “Existence theorem for a minimum problem with free discontinuity set", Arch. Rat. Mech. Anal., 108 (1989), 195-218.
4. L. M. J. Florac, A. H. Salden, B. M. ter Haar Romeny, J. J. Koenderink and M. A. Viergever, “Nonlinear Scale-Space",Image and Vision Computing, 13 (1995) 279-294.
5. H Helmholtz von, “Handbuch der Psychologischen Optik", Voss, Hamburg, 1896.
6. R Kimmel and R Malladi and N Sochen, “Images as Embedding Maps and Minimal Surfaces: Movies, Color, Texture, and Volumetric Medical Images", Proc. of IEEE CVPR’97, (1997) 350-355.
7. R Kimmel and N Sochen and R Malladi, “On the geometry of texture", Report, Berkeley Labs. UC, LBNL-39640, UC-405, November,1996.
8. R Kimmel and N Sochen and R Malladi, “From High Energy Physics to Low Level Vision", Lecture Notes In Computer Science: 1252, First International Conference on Scale-Space Theory in Computer Vision, Springer-Verlag, 1997, 236-247.
9. R Kimmel, “A natural norm for color processing", Proc. of 3-rd Asian Conf. on Computer Vision, Hong Kong, Springer-Verlag, LNCS 1351, 1998, 88-95.
10. E Kreyszing, “Diérential Geometry", Dover Publications, Inc., New York, 1991.
11. J. M. Morel and S. Solimini, Variational methods in image segmentation, Birkhauser, Boston, MA, 1995.
12. D. Mumford and J. Shah, “Optimal approximations by piecewise smooth functions and associated variational problems," Comm. Pure Appl. Math., 42 (1989), 577-685.
13. A M Polyakov, “Quantum geometry of bosonic strings", Physics Letters, 103B (1981) 207-210.
14. M Proesmans and E Pauwels and L van Gool, “Coupled geometry-driven Diffusion equations for low level vision", In Geometric-Driven Diffusion in Computer Vision, Ed. B M ter Haar Romeny, Kluwer Academic Publishers, 1994.
15. T Richardson and S Mitter, “Approximation, computation, and distortion in the variational formulation", In Geometric-Driven Diffusion in Computer Vision, Ed. B M ter Haar Romeny, Kluwer Academic Publishers, 1994.
16. Geometric-Driven Diffusion in Computer Vision, Ed. B M ter Haar Romeny, Kluwer Academic Publishers, 1994.
17. L Rudin and S Osher and E Fatemi, “Nonlinear total variation based noise removal algorithms", Physica D, 60 (1991) 259-268.
18. N Sochen and R Kimmel and R Malladi, “From high energy physics to low level vision", Report, LBNL, UC Berkeley, LBNL 39243, August, Presented in ONR workshop, UCLA, Sept. 5 1996.
19. N Sochen and R Kimmel and R Malladi, “A general framework for low level vision", IEEE Trans. on Image Processing, 7, (1998) 310-318.
20. N Sochen and Y Y Zeevi, “Images as manifolds embedded in a spatial-feature non-Euclidean space", November 1998, EE-Technion report no. 1181.
21. N Sochen and Y Y Zeevi, “Representation of colored images by manifolds embed-ded in higher dimensional non-Euclidean space", IEEE ICIP’98, Chicago, 1998.
22. W S Stiles, “A modiéd Helmholtz line element in brightness-colour space, Proc. Phys. Soc. (London), 58 (1946) 41.
23. G Wyszecki and W S Stiles, “Color Science: Concepts and Methods, Qualitative Data and Formulae", (2nd edition), Jhon Wiley & Sons, 1982.
24. A Yezzi, “Modiéd curvature motion for image smoothing and enhancement", IEEE Trans. on Image Processing, 7 (1998) 345-352.