blurring techniques
DESCRIPTION
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 - PowerPoint PPT PresentationTRANSCRIPT
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
Draw viewer’s attention to a particular place
Example
without blurring with blurring
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
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
The Finite Aperture Camera Model
Depth of field
Circle of confusion
Synthetic Image Generation
1. Hidden-Surface Processor
Synthetic Image Generation
2. Focus Processor
Example
Distributed ray tracing
Thin Lens Approximation
Thin Lens Approximation
Thick Lens Approximation
Thick Lens Approximation
Full Lens Systems
Full Lens Systems
Example
Object space blurring’s defects Computationally expensive
The increase in computation cost is proportional to the number of rays per pixel
Image space blurring
Image Depth Information
Image separated by depth
Final blurred image
Problems with image space blurring techniques
1. Occlusion problem
Problems with image space blurring techniques
2. Discretization Problem
Problems with image space blurring techniques
2. Discretization Problem
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
Edge detection technique
Get edges of subimages Use Canny edge detection algorithm
Edge detection technique
Extend the region
Example
Original image and depth information
Example
Blurred image without object identification
Example
Blurred image with object identification
Adjacent pixel difference technique
Use depth’s difference
Set the bound, adjacent pixels within the bound belong to the same object
Example
Example: Original Image
Example: blur without object identification
Example: blur with object identification
Example: blur with object identification