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Blurring Techniques

Blurring Techniques. Zhenyu Shu 2006.4.17. Scene Rendering. Object Space -> Image Space Method: Scan line rendering, Ray tracing, etc Traditional method focused at all depth without depth of field. Advantage of Blurring. Add realism to a scene

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Blurring Techniques

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  1. Blurring Techniques Zhenyu Shu 2006.4.17

  2. Scene Rendering • Object Space -> Image Space • Method: Scan line rendering, Ray tracing, etc • Traditional method focused at all depth without depth of field

  3. Advantage of Blurring • Add realism to a scene • Draw viewer’s attention to a particular place

  4. Example without blurring with blurring

  5. How to add blurring? • Object Space • Synthetic Image Generation with and Aperture Camera Model, M. Potmesil, I. Chakravarty, 1981, Siggraph • Distributed Ray Tracing, R.L. Cook, 1984, Siggraph • Camera Models and Optical Systems Used in Computer Graphics: Part I, Object-Based Techniques, Brian A. Barsky, Daniel R. Horn, Stanley A. Klein;Jerrey A. Pang,and Meng Yu, 2003, ICCSA

  6. How to add blurring? • Image space • Camera Models and Optical Systems Used in Computer Graphics: Part II, Image-Based Techniques, Brian A. Barsky, Daniel R. Horn, Stanley A. Klein;Jerrey A. Pang,and Meng Yu, 2003, ICCSA • Elimination of artifacts due to occlusion and discretization problems in image space blurring techniques, Brian A. Barsky, Michael J. Tobias, Derrick P. Chu, Daniel R. Horn, 2005, Graphical Models

  7. The Finite Aperture Camera Model

  8. Depth of field

  9. Circle of confusion

  10. Synthetic Image Generation • 1. Hidden-Surface Processor

  11. Synthetic Image Generation • 2. Focus Processor

  12. Example

  13. Distributed ray tracing

  14. Thin Lens Approximation

  15. Thin Lens Approximation

  16. Thick Lens Approximation

  17. Thick Lens Approximation

  18. Full Lens Systems

  19. Full Lens Systems

  20. Example

  21. Object space blurring’s defects • Computationally expensive • The increase in computation cost is proportional to the number of rays per pixel

  22. Image space blurring Image Depth Information

  23. Image separated by depth

  24. Final blurred image

  25. Problems with image space blurring techniques • 1. Occlusion problem

  26. Problems with image space blurring techniques • 2. Discretization Problem

  27. Problems with image space blurring techniques • 2. Discretization Problem

  28. How to eliminate artifacts • 1. Object Identification: detect large objects straddling several sub-images • 1.1 Edge detection technique • 1.2 Adjacent pixel difference technique • 2. Extend each sub-images and blur respectively

  29. Edge detection technique • Get edges of subimages • Use Canny edge detection algorithm

  30. Edge detection technique • Extend the region

  31. Example • Original image and depth information

  32. Example • Blurred image without object identification

  33. Example • Blurred image with object identification

  34. Adjacent pixel difference technique • Use depth’s difference • Set the bound, adjacent pixels within the bound belong to the same object

  35. Example

  36. Example: Original Image

  37. Example: blur without object identification

  38. Example: blur with object identification

  39. Example: blur with object identification

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