1 Image Formation. 2 Objectives Fundamental imaging notions Physical basis for image formation ­Light ­Color ­Perception Synthetic camera model Other.

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Presentation transcript:

1 Image Formation

2 Objectives Fundamental imaging notions Physical basis for image formation ­Light ­Color ­Perception Synthetic camera model Other models

3 Image Formation In computer graphics, we form images which are generally two dimensional using a process analogous to how images are formed by physical imaging systems ­Cameras ­Microscopes ­Telescopes ­Human visual system

4 Elements of Image Formation Objects Viewer Light source(s) Attributes that govern how light interacts with the materials in the scene Note the independence of the objects, the viewer, and the light source(s)

5 Light Light is the part of the electromagnetic spectrum that causes a reaction in our visual systems Generally these are wavelengths in the range of about nm (nanometers) Long wavelengths appear as reds and short wavelengths as blues

6 Ray Tracing and Geometric Optics One way to form an image is to follow rays of light from a point source finding which rays enter the lens of the camera. However, each ray of light may have multiple interactions with objects before being absorbed or going to infinity.

7 Luminance and Color Images Luminance Image ­Monochromatic ­Values are gray levels ­Analogous to working with black and white film or television Color Image ­Has perceptional attributes of hue, saturation, and lightness ­Do we have to match every frequency in visible spectrum? No!

8 Three-Color Theory Human visual system has two types of sensors ­Rods: monochromatic, night vision ­Cones Color sensitive Three types of cones Only three values (the tristimulus values) are sent to the brain Need only match these three values ­Need only three primary colors

9 Shadow Mask CRT

10 Additive and Subtractive Color Additive color ­Form a color by adding amounts of three primaries CRTs, projection systems, positive film ­Primaries are Red (R), Green (G), Blue (B) Subtractive color ­Form a color by filtering white light with cyan (C), Magenta (M), and Yellow (Y) filters Light-material interactions Printing Negative film

11 Pinhole Camera x p = -x/z/dy p = -y/z/d Use trigonometry to find projection of point at (x,y,z) These are equations of simple perspective z p = d

12 Synthetic Camera Model center of projection image plane projector p projection of p

13 Advantages Separation of objects, viewer, light sources Two-dimensional graphics is a special case of three-dimensional graphics Leads to simple software API ­Specify objects, lights, camera, attributes ­Let implementation determine image Leads to fast hardware implementation

14 Global vs. Local Lighting Cannot compute color or shade of each object independently ­Some objects are blocked from light ­Light can reflect from object to object ­Some objects might be translucent

15 Why not ray tracing? Ray tracing seems more physically based so why don’t we use it to design a graphics system? Possible and is actually simple for simple objects such as polygons and quadrics with simple point sources In principle, can produce global lighting effects such as shadows and multiple reflections but ray tracing is slow and not well-suited for interactive applications