colorization using optimization

Colorization using Optimization Anat Levin Dani Lischinski Yair - PowerPoint PPT Presentation

Colorization using Optimization Anat Levin Dani Lischinski Yair Weiss Colorization Colorization : a computer-assisted process of adding color to a monochrome image or ) movie. (Invented by Wilson Markle, 1970 Motivation Colorizing black


  1. Colorization using Optimization Anat Levin Dani Lischinski Yair Weiss

  2. Colorization Colorization : a computer-assisted process of adding color to a monochrome image or ) movie. (Invented by Wilson Markle, 1970

  3. Motivation • Colorizing black and white movies / TV shows • Recoloring color images for special effects

  4. Color 101 • Typically represented by points in a three dimensional color space : • ( Red , Green , Blue ) • Another option: [Y, U, V ] • Y - intensity • U, V - chromatic channels • A simple transformation exists: [R, G, B] ⇔ [Y, U, V ]

  5. Typical Colorization Process Images from: “Yet Another Colorization Tutorial ” http://www.worth1000.com/tutorial.asp?sid= 161018

  6. Typical Colorization Process • Delineate region boundary Images from: “Yet Another Colorization Tutorial ” http://www.worth1000.com/tutorial.asp?sid= 161018

  7. Typical Colorization Process • Delineate region boundary • Choose region color from palette Images from: “Yet Another Colorization Tutorial ” http://www.worth1000.com/tutorial.asp?sid= 161018

  8. Typical Colorization Process • Delineate region boundary • Choose region color from palette Images from: “Yet Another Colorization Tutorial ” http://www.worth1000.com/tutorial.asp?sid= 161018

  9. Typical Colorization Process • Delineate region boundary • Choose region color from palette Images from: “Yet Another Colorization Tutorial ” http://www.worth1000.com/tutorial.asp?sid= 161018

  10. Process Limitations • Requires expertise and time consuming • Selecting detailed or fuzzy boundaries is difficult • Tracking regions is difficult (for video )

  11. Our Approach Let the user focus on the creative goals, without having to worry about selection !

  12. Our Approach Colors are propagated to every pixel in the image . Grayscale channel Chroma channels

  13. Pixel Affinity Assumption: Neighboring pixels with similar intensities should have similar colors .

  14. Pixel Affinity s w rs r Minimize :

  15. Optimization • Find a function U that minimizes : (subject to the user’s color scribbles) • Boils down to solving a system of linear equations . • Do the same for V .

  16. Colorizing Stills

  17. Colorizing Stills Original Colorized

  18. Colorizing Stills

  19. Colorizing Video out of 92 frames 13

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