Digital image processing
From Includipedia, the inclusionist encyclopedia
Digital image processing is the use of computer algorithms to perform image processing on digital images. Digital image processing has the same advantages over analog image processing as digital signal processing has over analog signal processing — it allows a much wider range of algorithms to be applied to the input data, and can avoid problems such as the build-up of noise and signal distortion during processing.
The most common kind of digital image processing is digital image editing.
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History
Many of the techniques of digital image processing, or digital picture processing as it was often called, were developed in the 1960s at the Jet Propulsion Laboratory, MIT, Bell Labs, University of Maryland, and a few other places, with application to satellite imagery, wirephoto standards conversion, medical imaging, videophone, character recognition, and photo enhancement.[1] But the cost of processing was fairly high with the computing equipment of that era. In the 1970s, digital image processing proliferated, when cheaper computers and dedicated hardware became available. Images could then be processed in real time, for some dedicated problems such as television standards conversion. As general-purpose computers became faster, they started to take over the role of dedicated hardware for all but the most specialized and compute-intensive operations.
With the fast computers and signal processors available in the 2000s, digital image processing has become the most common form of image processing, and is generally used because it is not only the most versatile method, but also the cheapest.
Digital processing of camera images
Digital cameras generally include dedicated digital image processing chips to convert the raw data from the image sensor into a color-corrected image in a standard image file format. Images from digital cameras often receive further processing to improve their quality, a distinct advantage digital cameras have over film cameras. The digital image processing is typically done by special software programs that can manipulate the images in many ways.
Many digital cameras also enable viewing of histograms of images, as an aid for the photographer to better understand the rendered brightness range of each shot.
Uses
Digital Image Processing allows the use of much more complex algorithms for image processing, and hence can offer both more sophisticated performance at simple tasks, and the implementation of methods which would be impossible by analog means.
In particular, digital image processing is the only practical technology for:
Some techniques which are used in digital image processing include:
- Principal components analysis
- Independent component analysis
- Self-organizing maps
- Hidden Markov models
- Neural networks
See also
- Computer graphics
- Computer vision
- GPGPU
- Homomorphic filtering
- Imaging
- Satellite imagery
- Machine vision glossary
References
Sorted alphabetically with respect to first author's family name
- Wilhelm Burger and Mark J. Burge (2007). Digital Image Processing: An Algorithmic Approach Using Java. Springer. ISBN 1846283795.
- Rafael C. Gonzalez, Richard E. Woods (1992). Digital Image Processing. ISBN 0-201-50803-6.
- William K. Pratt (1978). Digital Image Processing. ISBN 0-471-01888-0.
- John C. Russ (2006). The Image Processing Handbook. ISBN 0849372542.
- Jean Serra (1982). Image Analysis and Mathematical Morphology. ISBN 0126372403.
- (1988) Image Analysis and Mathematical Morphology Volume 2: Theoretical Advances. ISBN 0-12-637241-1.
- Bart M. ter Haar Romeny (2003). Front-End Vision and Multi-Scale Image Analysis. ISBN 1-4020-1507-0.
- Bart M. ter Haar Romeny (Ed.) (1994). Geometry-Driven Diffusion in Computer Vision. ISBN 0792330870.
- Ian T. Young, Jan J. Gerbrands, Lucas J. Van Vliet (1995). Fundamentals of Image Processing. ISBN 90-75691-01-7.
- ^ Azriel Rosenfeld, Picture Processing by Computer, New York: Academic Press, 1969
External links
- Lectures on Digital Image Processing: A collection of 18 lectures in pdf format from Vanderbilt University, by Alan Peters.
- Wikia has a wiki about this topic: Computer Vision
- CLIP - Classical Image Processing Library
- ComputerVisionWiki.org
| Digital signal processing |
|---|
| Theory — Discrete frequency | Nyquist–Shannon sampling theorem | estimation theory | detection theory |
| Sub-fields — audio signal processing | control engineering | digital image processing | speech processing | statistical signal processing |
| Techniques — Discrete Fourier transform (DFT) | Discrete-time Fourier transform (DTFT) | Impulse invariance | bilinear transform | Z-transform, advanced Z-transform |
| Sampling — oversampling | undersampling | downsampling | upsampling | aliasing | anti-aliasing filter | sampling rate | Nyquist rate/frequency |
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