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CG Term Project Fragment-Based Image Completion

CG Term Project Fragment-Based Image Completion. B89902008 徐士璿 B89902048 李懷平. Outline. Motivation Method Expected results Current results Reference. Motivation. Photo editing (Site Engineering) Using less space to store images Applications to digital communication.

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CG Term Project Fragment-Based Image Completion

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  1. CG Term ProjectFragment-Based Image Completion B89902008 徐士璿 B89902048 李懷平

  2. Outline • Motivation • Method • Expected results • Current results • Reference

  3. Motivation • Photo editing (Site Engineering) • Using less space to store images • Applications to digital communication

  4. Methods • Fast approximation • search for most similar fragment • Image composition

  5. Fast Approximation • Gaussian blur

  6. Fast Approximation (Cont.) • Gaussian filter

  7. Fast Approximation (Cont.) • Down sampling, up sampling, and pyramid

  8. Fast Approximation (Cont.) • Expected results:

  9. Search for Most Similar Fragment

  10. Image composition • Use α channel • Similar to transparency • Apply the equations to each level of the pyramid, and then reconstruct the image with it.

  11. Expected Results • Construct a plausible image • Apply to texture synthesis • Try to make the search faster - took about 2.5 hours for a 384 x 256 image ( > 0.7 with a 2.4GHz CPU)

  12. Current Results • Approximation

  13. Current Results (Cont.)

  14. Reference • DRORI, I., COHEN-OR, D., AND YESHURUN, H. 2003. Fragment-Based Image Completion. In Proceedings ofACM SIGGRAPH 2003. • GONZALEZ, R. C., AND WOODS, R. E. 2002. Digital Image Processing. Prentice Hall. • BURT, P. J., AND ADELSON, E. H. 1985. Merging images through pattern decomposition. Applications of Digital Image Processing VIII 575, 173–181.

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