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Colorization of black-and-white cartoons

Published: 01 September 2005 Publication History

Abstract

We introduce a novel colorization framework for old black-and-white cartoons originally produced by a cel or paper based technology. In this case, the dynamic part of the scene is represented by a set of outlined homogeneous regions which superimpose the static background. To reduce a large amount of manual intervention we combine unsupervised image segmentation, background reconstruction, and structural prediction. Our system allows the user to specify the brightness of applied colors unlike the most of previous approaches which operate only with hue and saturation. We also present simple but effective color modulation, composition and dust spot removal techniques able to produce color images in broadcast quality without additional user intervention.

References

[1]
Lenburg, L., The encyclopedia of animated cartoons. In: Facts on File, New York, NY,
[2]
Bancroft, D.J., Advanced and economical telecine technology for global DTV production. In: in: Broadcast Engineering Conference Proceedings,
[3]
Kokaram, A.C., . In: Motion Picture Restoration: Digital Algorithm for Artefact Suppression in Degraded Motion Picture Film and Video, Springer, London.
[4]
Markle, W., The development and application of colorization. SMPTE Journal. 632-635.
[5]
Cooper, R., Colorization and moral rights: should the united states adopt unified protection for artists?. Journalism Quarterly (Urbana, Illinois). v68. 465-473.
[6]
Leibowitz, F., Movie colorization and the expression of mood. Journal of Aesthetics and Art Criticism (Cleveland, Ohio). v49 i4. 363-364.
[7]
Gonzalez, R.C. and Woods, R.E., . In: Digital Image Processing, Addison-Wesley Publishing, Reading, MA.
[8]
Welsh, T., Ashikhmin, M. and Mueller, K., Transferring color to greyscale images. In: in: ACM SIGGRAPH 2002 Conference Proceedings,
[9]
Reinhard, E., Ashikhmin, M., Gooch, B. and Shirley, P., Color transfer between images. IEEE Transactions on Computer Graphics and Applications. v21 i5. 34-41.
[10]
Hertzmann, A., Jacobs, C.E., Oliver, N., Curless, B. and Salesin, D.H., Image analogies. In: in: ACM SIGGRAPH 2001 Conference Proceedings,
[11]
Markle, W. and Hunt, B., Coloring a black and white signal using motion detection. Canadian Patent No. CA 01291260.
[12]
Pan, Z., Dong, Z. and Zhang, M., A new algorithm for adding color to video or animation clips. In: in: Proceedings of WSCG-International Conference in Central Europe on Computer Graphics, Visualization and Computer Vision,
[13]
Horiuchi, T., Estimation of color for gray-level image by probabilistic relaxation. In: in: Proceedings of IEEE International Conference on Pattern Recognition,
[14]
Kittler, J. and Illingworth, J., Relaxation labelling algorithms-a review. Image and Vision Computing. v3. 206-216.
[15]
Horiuchi, T. and Hirano, S., Colorization algorithm for grayscale image by propagating seed pixels. In: in: Proceedings of IEEE International Conference on Pattern Recognition,
[16]
Levin, A., Lischinski, D. and Weiss, Y., Colorization using optimization. In: in: ACM SIGGRAPH 2004 Conference Proceedings,
[17]
Lucas, B.D. and Kanade, T., An iterative image registration technique with an application to stereo vision. In: in: Proceedings of the International Joint Conference on Artificial Intelligence,
[18]
G. Sapiro, Inpainting the colors, IMA Preprint Series #1979, Institute for Mathematics and its Applications, University of Minnesota, 2004. http://www.ima.umn.edu/preprints/may2004/may2004.html
[19]
Sapiro, G., . In: Geometric Partial Differential Equations and Image Processing, Cambridge University Press, Cambridge.
[20]
L. Yatziv, G. Sapiro, Fast Image and Video Colorization using Chrominance Blending, IMA Preprint Series #2010, Institute for Mathematics and its Applications, University of Minnesota, 2004. http://www.ima.umn.edu/preprints/dec2004/dec2004.html
[21]
Caselles, V., Kimmel, R. and Sapiro, G., Geodesic active contours. International Journal of Computer Vision. v22 i1. 61-79.
[22]
Chen, T., Wang, Y., Schillings, V. and Meinel, C., Grayscale image matting and colorization. In: in: Proceedings of Asian Conference on Computer Vision,
[23]
Chuang, Y.-Y., Curless, B., Salesin, D.H. and Szeliski, R., A Bayesian approach to digital matting. In: in: Processings of IEEE Conference on Computer Vision and Pattern Recognition,
[24]
Sýkora, D., Buriánek, J. and ¿ára, J., Segmentation of black and white cartoons. In: in: Proceedings of Spring Conference on Computer Graphics,
[25]
Marr, D. and Hildreth, E.C., . In: in: Proceedings of Royal Society, vol. B207.
[26]
Rosenfeld, A. and Kak, A.C., . In: Digital Picture Processing, vol. 1. Academic Press, Orlando.
[27]
Cheng, H.-D. and Sun, Y., A hierarchical approach to color image segmentation using homogeneity. IEEE Transactions on Image Processing. v9 i12. 2071-2082.
[28]
Witkin, A.P., Scale space filtering. In: Pentland, A.P. (Ed.), From Pixels to Predicates: Recent Advances in Computational and Robot Vision,
[29]
Clark, J.J., Authenticating edges produced by zero-crossing algorithms. IEEE Transactions on Pattern Analysis and Machine Intelligence. v11 i1. 43-57.
[30]
Sotak, G.E. and Boyer, K.L., The Laplacian-of-Gaussian kernel: a formal analysis and design procedure for fast, accurate convolution and full-frame output. Computer Vision, Graphics, and Image Processing. v48 i2. 147-189.
[31]
Chen, J.S., Huertas, A. and Medioni, G., Fast convolution with Laplacian-of-Gaussian masks. IEEE Transactions on Pattern Analysis and Machine Intelligence. v9 i4. 584-590.
[32]
D. King, Implementation of the Marr-Hildreth theory of edge detection, Tech. Rep. ISG-102, The University of Southern California, 1982.
[33]
Huertas, A. and Medioni, G., Detection of intensity changes with subpixel accuracy using Laplacian-Gaussian masks. IEEE Transactions on Pattern Analysis and Machine Intelligence. v8 i6. 651-664.
[34]
Serra, J., . In: Image Analysis and Mathematical Morphology, vol. 1. Academic Press, Oval Road.
[35]
Odobez, J.-M. and Bouthemy, P., Robust multiresolution estimation of parametric motion models. Journal of Visual Communication and Image Representation. v6 i4. 348-365.
[36]
Pérez, P., Gangnet, M. and Blake, A., Poisson image editing. In: in: ACM SIGGRAPH 2003 Conference Proceedings,
[37]
Levin, A., Zomet, A., Peleg, S. and Weiss, Y., Seamless image stitching in the gradient domain. In: in: Proceedings of European Conference on Computer Vision,
[38]
Burt, J.R. and Adelson, E.H., A multiresolution spline with application to image mosaics. ACM Transactions on Graphics. v2 i4. 217-236.
[39]
Reddy, B.S. and Chatterji, B.N., An FFT-based technique for translation, rotation and scale-invariant image registration. IEEE Transactions on Computers. v5 i8. 1266-1271.
[40]
Madeira, J.S., Stork, A. and Grob, M.H., An approach to computer-supported cartooning. The Visual Computer. v12. 1-17.
[41]
Chang, C.W. and Lee, S.Y., Automatic cel painting in computer-assisted cartoon production using similarity recognition. The Journal of Visualization and Computer Animation. v8. 165-185.
[42]
Seah, H.S. and Feng, T., Computer-assisted coloring by matching line drawings. The Visual Computer. v16. 289-304.
[43]
Qiu, J., Seah, H.S., Tian, F., Chen, Q. and Melikhov, K., Computer-assisted auto coloring by region matching. In: in: Proceedings of Pacific Conference on Computer Graphics and Applications,
[44]
Sýkora, D., Buriánek, J. and ¿ára, J., Unsupervised colorization of black-and-white cartoons. In: in: Proceedings of the Third International Symposium on Non-photorealistic Animation and Rendering,
[45]
C. Tomasi, T. Kanade, Shape and motion from image streams: a factorization method. Part 2. Detection and tracking of point features, Tech. Rep. CMU-CS-91-132, Carnegie Mellon University, School of Computer Science, 1991.
[46]
Ahmadyfard, A. and Kittler, J., Region-based object recognition: pruning multiple representations and hypotheses. In: in: Proceedings of British Machine Vision Conference,
[47]
Zitová, B. and Flusser, J., Image registration methods: a survey. Image and Vision Computing. v21. 977-1000.
[48]
Arya, S., Mount, D.M., Netanyahu, N.S., Silverman, R. and Wu, A.Y., An optimal algorithm for approximate nearest neighbor searching in fixed dimensions. Journal of the ACM. v45 i6. 891-923.
[49]
Kilthau, S.L., Drew, M.S. and Möller, T., Full search content independent block matching based on the fast Fourier transform. In: in: Proceedings of IEEE International Conference on Image Processing,
[50]
Nam, K.M., Kim, J.-S., Park, R.-H. and Shim, Y.S., A fast hierarchical motion vector estimation algorithm using mean pyramid. IEEE Transactions on Circuits and Systems for Video Technology. v5 i4. 344-351.
[51]
Chen, Y.-S., Hung, Y.-P. and Fuh, C.-S., Fast block matching algorithm based on the winner-update strategy. IEEE Transactions On Image Processing. v10 i8. 1212-1222.

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Information

Published In

cover image Image and Vision Computing
Image and Vision Computing  Volume 23, Issue 9
September, 2005
84 pages

Publisher

Butterworth-Heinemann

United States

Publication History

Published: 01 September 2005

Author Tags

  1. Color-by-example
  2. Colorization
  3. Edge detection
  4. Image analogies
  5. Image registration
  6. Image restoration
  7. Image segmentation
  8. Patch-based sampling
  9. Probabilistic relaxation

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