1. The Generic Sensor Each photosite converts lightwave energy into photo- electrons Pixels in the output image are a measure of the number of photo-electrons recorded at each photo site wells Light wells Sensors Problem: Since the sensor only records light intensity, we can’t differentiate between colors! Thus, digital cameras only record in black and white Solution: Color filtering, the most common form being the Bayer filter

2. 1)Designates individual photosites to be either red, green, or blue (RGB) 2)Respective color filters are placed over each photosite 3)Thus, only the light energy corresponding to that color’s wavelength reaches the sensor 4)Thus the sensor can interpret the energy recorded at that photosite to be a measure of that certain color

3. The Bayer Sensor wells Light wells Sensors

4. Color offset- light not recorded at the same spot -Demosaic algorithms required to interpolate missing data Discards 2/3 of light information -3x longer shutter speed, 3x larger aperture, 3x higher ISO D r a w b a c k s o f … Actual Image Raw Bayer Output Demosiaced Bayer Output

5. Linear Scanning Scans a scene with RGB linear sensors Gets full light information Slow, only works for static subjecs Alternative Color Filtering Technologies Bayer-like filters with different colors RGBC CYGM Same problems as Bayer filter Multi-shot approach Take three shots, each with different color filter Gets full light information Only works for static subjects, since a moving scene would change between filter switches

6. Alternative Color Filtering Technologies in Development Foveon sensor Uses vertically stacked RGB sensors Collects all light at each location Three-sensor Commonly known as “3CCD” Prism splits light, 3 sensors to record R,G,B

7. Color Temperature Light sources can be approximated as “black bodies” of a certain temperature Daylight: similar to 5000K black body (even light across the spectrum) Incandescent light: lower temperature (more red light, less blue) Shade/daylight: higher temperature (more blue light, less red) Human vision system makes corrections for different light sources Cameras aren’t so good at this

8. <- What we see What cameras see -> (interpreting all wavelengths equally)

9. White Balancing Auto-white balance White balance preset Color temperature Custom white balance RAW adjustment Last resort: color balance the JPEG