Example-based color stylization based on categorical perception

ABSTRACT

We describe a new computational approach to stylize the colors of an image by using a reference image. During processing, we take characteristics of human color perception into account to generate more appealing results. Our system starts by classifying each pixel value into one of a set of the basic color categories, derived from our psycho-physiological experiments. The basic color categories are perceptual categories that are universal to everyone, regardless of nationality or cultural background. These categories provide restrictions on the color transformations to avoid generating unnatural results. Our system then renders a new image by transferring colors from a reference image to the input image, based on this categorizations. To avoid artifacts due to the explicit clustering, our system defines fuzzy categorization when pseudo-contours appear in the resulting image. We present a variety of results and show that our color transformation performs a large, yet natural color transformation without any sense of incongruity, and that the resulting images automatically capture the characteristics of the color use of the reference image.

REFERENCES

• 1: ANALOGIES-WEB-PAGE. http://mrl.nyu.edu/projects/imageanalogies/.
• 2: ARTCHIVE. http://www.artchive.com/.
• 3: BERLIN, B., AND KAY, P. 1969. Basic Color Terms: Their Universality and Evolution. University of California Press.
• 4: CHANG, Y., SAITO, S., AND NAKAJIMA, M. 2002. Color transformation based on the basic color categories of a painting. In ACM SIGGRAPH Conference Abstracts and Applications, 157.
• 5: CHANG, Y., SAITO, S., AND NAKAJIMA, M. 2003. A framework for transfer colors based on the basic color categories. In Computer Graphics International, 176--183.
• 6: CURTIS, C. J., ANDERSON, S. E. SEIMS, J. E., FLEISCHER, K. W., AND SALESIN, D. H. 1997. Computer-generated watercolor. 421--430.
• 7: FAIRCHILD, M. D. 1997. Color Appearance Models. Addison-Wesley.
• 8: Bruce Gooch , Amy Gooch, Non-Photorealistic Rendering, A. K. Peters, Ltd., Natick, MA, 2001
• 9: HAEBERLI, P. 1990. Paint by numbers:abstract image representation. 207--214.
• 10: Aaron Hertzmann , Charles E. Jacobs , Nuria Oliver , Brian Curless , David H. Salesin, Image analogies, Proceedings of the 28th annual conference on Computer graphics and interactive techniques, p.327-340, August 2001 [doi>10.1145/383259.383295]
• 11: Aaron Hertzmann, Painterly rendering with curved brush strokes of multiple sizes, Proceedings of the 25th annual conference on Computer graphics and interactive techniques, p.453-460, July 1998 [doi>10.1145/280814.280951]
• 12: ICHIMURA, N. 1997. Region segmentation method using both feature space and image space based on robust clustering. In IEICE Transaction on Information and Systems, vol. J80-D2, 1752--1763.
• 13: Peter Litwinowicz, Processing images and video for an impressionist effect, Proceedings of the 24th annual conference on Computer graphics and interactive techniques, p.407-414, August 1997 [doi>10.1145/258734.258893]
• 14: MARIO C. SOUSA, J. W. B. 1999. Computer-generated graphite pencil rendering of 3d polygonal models. In Computer Graphics Forum, 195--208.
• 15: MARIO C. SOUSA, J. W. B. 2000. Observational models of graphite pencil materials. In Computer Graphics Forum, 27--49.
• 16: MEIER, B. J. 1996. Painterly rendering for animation. vol. 30, 477--484.
• 17: P. Perona , J. Malik, Scale-Space and Edge Detection Using Anisotropic Diffusion, IEEE Transactions on Pattern Analysis and Machine Intelligence, v.12 n.7, p.629-639, July 1990 [doi>10.1109/34.56205]
• 18: Erik Reinhard , Michael Ashikhmin , Bruce Gooch , Peter Shirley, Color Transfer between Images, IEEE Computer Graphics and Applications, v.21 n.5, p.34-41, September 2001
• 19: ROSCH HEIDER, E. 1972. Universals in color naming and memory. In Journal of Experimental Psychology, vol. 93, 10--20.
• 20: SAITO, S., AND NAKAJIMA, M. 1996. Automatic production of hand-painted images. In The Journal of the Institute of Television Engineers of Japan, vol. 50, 1528--1535.
• 21: TERRA-GALLERIA. http://www.terragalleria. com/.
• 22: UCHIKAWA, K., AND BOYNTON, R. M. 1987. Categorical color perception of japanese observers: Comparison with that of americans. In Vision Research, vol. 27, 1825--1833.
• 23: UCHIKAWA, K., KURIKI, I., AND SHINODA, H. 1994. Expression of color appearance in aperture and surface color modes with a category rating estimation method. Springer-Verlag, vol. 78, 41--51.
• 24: Tomihisa Welsh , Michael Ashikhmin , Klaus Mueller, Transferring color to greyscale images, ACM Transactions on Graphics (TOG), v.21 n.3, July 2002

INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.3 COMPUTER GRAPHICS
      I.3.3 Picture/Image Generation

Additional Classification:
  I. Computing Methodologies
  I.4 IMAGE PROCESSING AND COMPUTER VISION
        I.4.10 Image Representation
            Subjects: Statistical
      I.4.5 Reconstruction
          Subjects: Transform methods
      I.4.6 Segmentation
          Subjects: Pixel classification

Keywords:
basic color category, color transfer, example-based