Digital Cameras

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Digital Cameras

• Engineering Math Physics (EMP)
• Jennifer Rexford
• http//www.cs.princeton.edu/jrex

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Image Transmission Over Wireless Networks

• Image capture and compression
• Inner-workings of a digital camera
• Manipulating transforming a matrix of pixels
• Implementing a variant of JPEG compression
• Wireless networks
• Wireless technology
• Acoustic waves and electrical signals
• Radios
• Video over wireless networks
• Video compression and quality
• Transmitting video over wireless
• Controlling a car over a radio link

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Traditional Photography

• A chemical process, little changed from 1826
• Taken in France on a pewter plate
• with 8-hour exposure

The world's first photograph
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Digital Photography

• Digital photography is an electronic process
• Only widely available in the last ten years
• Digital cameras now surpass film cameras in sales

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Image Formation
Digital Camera
Film
Eye
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Aperture and Exposure

• Aperture
• Diameter of the hole allowing light to enter
• E.g., the pupil of the eye
• Higher aperture leads to more light entering
• though poorer focus across a wider depth of
  field
• Shutter speed
• Time for light to enter the camera
• Longer times lead to more light
• though blurring of moving subjects
• Together, determine the exposure
• The amount of light allowed to enter the camera

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Image Formation in a Pinhole Camera

• Light enters a darkened chamber through pinhole
  opening and forms an image on the further surface

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Image Formation in a Digital Camera
10V
Photon

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CCD sensor

• Array of sensors
• Light-sensitive diodes that convert photons to
  electrons
• Each cell corresponds to a picture element
  (pixel)
• Sensor technologies
• Charge Coupled Device (CCD)
• Complementary Metal Oxide Semiconductor (CMOS)

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Sensor Array Image Sampling
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Sensor Array Reading Out the Pixels

• Transfer the charge from one row to the next
• Transfer charge in the serial register one cell
  at a time
• Perform digital to analog conversion one cell at
  a time
• Store digital representation

Digital-to-analog conversion
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Sensor Array Reading Out the Pixels
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More Pixels Mean More Detail
1280 x 960
1600 x 1400
640 x 480
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The 320 x 240hand
The 2272 x 1704hand
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Representing Color

• Light receptors in the human eye
• Rods sensitive in low light, mostly at periphery
  of eye
• Cones only at higher light levels, provide color
  vision
• Different types of cones for red, green, and blue
• RGB color model
• A color is some combination of red, green, and
  blue
• E.g., eight bits for each color
• With 28 256 values
• Corresponding to intensity
• Leading to 24 bits per pixel
• Red 255, 0, 0
• Green 0, 255, 0
• Yellow 255, 255, 0

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Number of Bits Per Pixel

• Number of bits per pixel
• More bits can represent a wider range of colors
• 24 bits can capture 224 16,777,216 colors
• Most humans can distinguish around 10 million
  colors

8 bits / pixel / color
4 bits / pixel / color
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Separate Sensors Per Color

• Expensive cameras
• A prism to split the light into three colors
• Three CCD arrays, one per RGB color

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Practical Color Sensing Bayer Grid

• Place a small color filter over each sensor
• Each cell captures intensity of a single color
• More green pixels, since human eye is better at
  resolving green

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Practical Color Sensing Interpolating

• Challenge estimating pixels we do not know for
  certain
• For a non-green cell, look at the neighboring
  green cells
• And, interpolate the value
• Accuracy of interpolation
• Good in low-contrast areas
• Poor with sharp edges (e.g., text)

Estimate RGB at the G cells from neighboring
values
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Digital Images Require a Lot of Storage

• Three dimensional object
• Width (e.g., 640 pixels)
• Height (e.g., 480 pixels)
• Bits per pixel (e.g., 24-bit color)
• Storage is the product
• Pixel width pixel height bits/pixel
• Divided by 8 to convert from bits to bytes
• Common sizes
• 640 x 480 1 Megabyte
• 800 x 600 1.5 Megabytes
• 1600 x 1200 6 Megabytes

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Compression

• Benefits of reducing the size
• Consume less storage space and network bandwidth
• Reduce the time to load, store, and transmit the
  image
• Redundancy in the image
• Neighboring pixels often the same, or at least
  similar
• E.g., the blue sky
• Human perception factors
• Human eye is not sensitive to high frequencies

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Contrast Sensitivity Curve
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Lossy vs. Lossless Compression

• Lossless
• Only exploits redundancy in the data
• So, the data can be reconstructed exactly
• Necessary for most text documents (e.g., legal
  documents, computer programs, and books)
• Lossy
• Exploits both data redundancy and human
  perception
• So, some of the information is lost forever
• Acceptable for digital audio, images, and video

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Examples of Lossless Compression

• Huffman encoding
• Assign fewer bits to less-popular symbols
• E.g., a occurs more often than i
• so encode a as 000 and i as 00111
• Efficient when probabilities vary widely
• Run-length encoding
• Identify repeated occurrences of the same symbol
• Capture the symbol and the number of repetitions
• E.g., eeeeeee ? _at_e7
• E.g., eeeeetnnnnnn ? _at_e5t_at_n6

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Joint Photographic Experts Group

• Lossy compression of images
• Starts with an array of pixels in RGB format
• With one number per pixel for each of the three
  colors
• Outputs a smaller file with some loss in quality
• Exploits both redundancy and human perception
• Transforms the data to identify parts that humans
  notice less
• More about transforming the data in Wednesdays
  class

Uncompressed 167 KB
Good quality 46 KB
Poor quality 9 KB
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Conclusion

• Digital cameras
• Light and a optical lens
• Charge and electronic devices
• Pixels and a digital computer
• Digital images
• A two-dimensional array of pixels
• Red, green, and blue intensities for each picture
• Image compression
• Raw images are very large
• Compression reduces the image size substantially
• By exploiting redundancy and human perception