The 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 (Source: http://en.wikipedia.org/wiki/Digital_image_processing).

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.[1] 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 (Source: http://en.wikipedia.org/wiki/Digital_image_processing).

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 (Source: http://en.wikipedia.org/wiki/Digital_image_processing).

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 (Source: http://en.wikipedia.org/wiki/Digital_image_processing).

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:

PixelizationLinear filtering
Principal components analysis
Independent component analysis
Hidden Markov models
Anisotropic diffusion
Partial differential equations
Self-organizing maps
Neural networks
Wavelets.

(Source: http://en.wikipedia.org/wiki/Digital_image_processing)

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