Digital image processing

This article is about mathematical processing of digital images. For artistic processing of images, see Image editing.

Digital image processing is the use of computer algorithms to perform image processing on digital images. As a subcategory or field of digital signal processing, digital image processing has many advantages over analog image 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. Since images are defined over two dimensions (perhaps more) digital image processing may be modeled in the form of multidimensional systems.

History

Many of the techniques of digital image processing, or digital picture processing as it often was called, were developed in the 1960s at the Jet Propulsion Laboratory, Massachusetts Institute of Technology, Bell Laboratories, University of Maryland, and a few other research facilities, with application to satellite imagery, wire-photo standards conversion, medical imaging, videophone, character recognition, and photograph enhancement. The cost of processing was fairly high, however, with the computing equipment of that era. That changed in the 1970s, when digital image processing proliferated as cheaper computers and dedicated hardware became available. Images then could 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 computer-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 generally, is used because it is not only the most versatile method, but also the cheapest.

Digital image processing technology for medical applications was inducted into the Space Foundation Space Technology Hall of Fame in 1994.

Tasks

Digital image processing allows the use of much more complex algorithms, 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:

• Classification
• Feature extraction
• Pattern recognition
• Projection
• Multi-scale signal analysis

Some techniques which are used in digital image processing include:

• Pixelation
• Linear filtering
• Principal components analysis
• Independent component analysis
• Hidden Markov models
• Anisotropic diffusion
• Partial differential equations
• Self-organizing maps
• Neural networks
• Wavelets
• Multiplicative calculus

Applications

Further information: Digital imaging

Digital camera images

Digital cameras generally include dedicated digital image processing chips to convert the raw data from the image sensor into a colour-corrected image in a standard image file format. Images from digital cameras often receive further processing to improve their quality, a distinct advantage that digital cameras have over film cameras. The digital image processing typically is executed 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 understand the rendered brightness range of each shot more readily.

Film

Westworld (1973) was the first feature film to use digital image processing to pixellate photography to simulate an android's point of view.

Intelligent transportation systems

Digital image processing has a wide applications in intelligent transportation systems, such as automatic number plate recognition and traffic sign recognition.

See also

• Computer graphics
• Computer vision
• Digitizing
• Comparison of image processing software
• GPGPU
• Homomorphic filtering
• Standard test image
• Superresolution
• Multidimensional systems
• IEEE Intelligent Transportation Systems Society

Further reading

• Solomon, C.J., Breckon, T.P. (2010). Fundamentals of Digital Image Processing: A Practical Approach with Examples in Matlab. Wiley-Blackwell. doi:10.1002/9780470689776. ISBN 0470844736. 

• Wilhelm Burger and Mark J. Burge (2007). Digital Image Processing: An Algorithmic Approach Using Java. Springer. ISBN 1-84628-379-5 and ISBN 3-540-30940-3 . 
• R. Fisher, K Dawson-Howe, A. Fitzgibbon, C. Robertson, E. Trucco (2005). Dictionary of Computer Vision and Image Processing. John Wiley. ISBN 0-470-01526-8. 
• Bernd Jähne (2002). Digital Image Processing. Springer. ISBN 3-540-67754-2. 
• Tim Morris (2004). Computer Vision and Image Processing. Palgrave Macmillan. ISBN 0-333-99451-5. 
• Milan Sonka, Vaclav Hlavac and Roger Boyle (1999). Image Processing, Analysis, and Machine Vision. PWS Publishing. ISBN 0-534-95393-X. 
• Rafael C. Gonzalez, Richard E. Woods and Steven L. Eddins (2004). Digital Image Processing using MATLAB. Pearson Education. ISBN 978-81-7758-898-9. 
• Luc Florack and Hans van Assen (2011). ""Multiplicative calculus in biomedical image analysis"". Journal of Mathematical Imaging and Vision. 

External links

• Lectures on Image Processing, by Alan Peters. Vanderbilt University. Updated 11 March 2013.
• Tutorial for image processing (contains a Java applet)
• IPRG Open group related to image processing research resources