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Digital Cameras
An Introduction


Prof. David Bernstein
James Madison University

Computer Science Department
bernstdh@jmu.edu

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Sight
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  • The Eye:
    • images/eye.gif
  • The Process within the Eye:
    • Light enters through the cornea
    • Is focused by the lens
    • Stimulates sensors in the retina
Sight (cont.)
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  • Rods:
    • Stimulated by short wavelengths
    • Respond quickly
    • Output imacts our perception of luminance/brightness
  • Cones:
    • \(\beta\) sensors are sensitive to wavelengths between 400 and 550 nm, but are most sensitive to a wavelength of 450 nm (what we call blue)
    • \(\gamma\) sensors are sensitive to wavelengths between 420 and 660 nm, but are most sensitive to a wavelength of 540 nm (what we call green)
    • \(\rho\) sensors are sensitive to wavelengths between 400 and 700 nm, but are most sensitive to a wavelength of 580 nm (what we call red)
Digitizing Visual Content
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  • An Implication:
    • When presenting visual content it makes sense to use an output device that generates/reflects red, green, and blue light
  • A Further Implication:
    • When digitizing (and storing) visual content it makes sense to use a sensor that measures red, green, and blue light
Modeling Color
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The (Linear) Color Cube

images/rgb-cube.gif
Modeling Color (cont.)
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  • The RGB Model:
    • Begin with black then add red, green, and or blue
    • An additive model
    • Often used for displays/monitors
  • The CMYK Model:
    • Begin with white then remove cyan, magenta, and/or yellow
    • A subtractive model
    • Often used for printing
Camera Basics
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  • The Shutter:
    • Creates a hole (called the aperture) that allows light to enter
  • The Lens:
    • Focuses the light
Sensors in a Digital Camera
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  • Two Main Types:
    • Charge-Coupled Devices (CCDs)
    • Complementary Metal-Oxide-Semiconductor (CMOS) Image Sensor
  • Commonalities and Differences:
    • Each has a rectangular grid (the size of which determines the resolution) of photosites (called picture elements, or pixels) that convert light to electricity
    • CMOS sensors have an amplifier for each pixel; CCD pixels have amplifiers for entire rows of sensors
Tradeoffs
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  • Noise:
    • CMOS sensors are more susceptible to noise
  • Light Sensitivity:
    • CMOS sensors have lower light sensitivity (because some of the light hits the amplifiers)
  • Power Consumption:
    • CMOS sensors consume less power
Measuring Color
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  • Using Layered Sensors (e.g., Foveon X3):
    • The wavelength-dependent absoroption properties of the silicon are used to separate the light to the three layers, each of which measures a different color
  • Using a Beam Splitter (e.g. 3CCD):
    • The beam splitter creates three paths for the light
    • Each path is directed to a different sensor with a different filter (i.e., red, green, or blue)
  • Using a Rotating Filter:
    • Red, green, and blue filters are rotated in front of a single sensor in quick succession
  • Using a Filter Array:
    • A fixed filter grid is placed in front of a single sensor so that each photosite measures a different color
The Bayer Filter
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  • Visualization:
    • images/BayerFilter.png
  • Properties:
    • Has as many green pixels as red and blue combined (because the eye is not equally sensitive to all three colors)
  • A Simple Demosaicing Algorithm:
    • One color is measured exactly
    • The amounts of the other two colors are obtained by interpolating the neighbors of that color
Storage
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  • In Raw Format:
    • Each pixel requires storage for its red, blue, and green components
  • Representation of Each Component:
    • Typically one byte (256 different values)
  • Total Storage:
    • The resolution times three (e.g., a 10 megapixel camera would require 30 megabytes for an image)
Compression
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  • The Idea:
    • Reduce the amount of space required to store an image
  • Approaches:
    • Lossless(e.g., .png)
    • Lossy (e.g., Most JPEG algorithms)
Compression (cont.)
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  • A Simple Lossless Algorithm:
    • Run Length Encoding - replace a sequence of pixels of the same color with the color and the number of times it repeats
  • A Simple Lossy Algorithm:
    • Discard every \(n^{\text{th}}\) pixel
There's Always More to Learn
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