Digital Cameras - PowerPoint PPT Presentation

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Digital Cameras

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Inner-workings of a digital camera. Manipulating & transforming a matrix of pixels ... Image Formation in a Digital Camera. Array of sensors ... – PowerPoint PPT presentation

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Title: Digital Cameras


1
Digital Cameras
  • Engineering Math Physics (EMP)
  • Jennifer Rexford
  • http//www.cs.princeton.edu/jrex

2
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

3
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
4
Digital Photography
  • Digital photography is an electronic process
  • Only widely available in the last ten years
  • Digital cameras now surpass film cameras in sales

5
Image Formation
Digital Camera
Film
Eye
6
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

7
Image Formation in a Pinhole Camera
  • Light enters a darkened chamber through pinhole
    opening and forms an image on the further surface

8
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)

9
Sensor Array Image Sampling
10
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
11
Sensor Array Reading Out the Pixels
12
More Pixels Mean More Detail
1280 x 960
1600 x 1400
640 x 480
13
The 320 x 240hand
The 2272 x 1704hand
14
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

15
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
16
Separate Sensors Per Color
  • Expensive cameras
  • A prism to split the light into three colors
  • Three CCD arrays, one per RGB color

17
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

18
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
19
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

20
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

21
Contrast Sensitivity Curve
22
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

23
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

24
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
25
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
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