From Wikipedia, the free encyclopedia
In the broadest sense, image processing is any form of information processing for which both the input and output are images, such as photographs or frames of video. Most image processing techniques involve treating the image as a two-dimensional signal and applying standard signal processing techniques to it.
A few decades ago, image processing was done largely in the analog domain, chiefly by optical devices. These optical methods are still essential to applications such as holography because they are inherently parallel; however, due to the significant increase in computer speed, these techniques are increasingly being replaced by digital image processing methods.
Digital image processing techniques are generally more versatile, reliable, and accurate; they have the additional benefit of being easier to implement than their analog counterparts. Specialized hardware is still used for digital image processing: computer architectures based on pipelining have been the most commercially successful. There are also many massively parallel architectures that have been developed for the purpose. Today, hardware solutions are commonly used in video processing systems. However, commercial image processing tasks are more commonly done by software running on conventional personal computers.
Commonly-used signal processing techniques
Most of the signal processing concepts that apply to one-dimensional signals also extend to the two-dimensional image signal. Some of these one-dimensional signal processing concepts become significantly more complicated in two-dimensional processing. Image processing brings some new concepts, such as connectivity and rotational invariance, that are meaningful only for two-dimensional signals.
The Fourier transform, using coherent optics or digital fast fourier transform, is often used for image processing operations involving large-area correlation.
- Dynamic range
- Differential operators
- Edge detection
- Domain modulation
- Noise reduction
- Rotational invariance
- Geometric transformations such as enlargement, reduction, and rotation
- Color corrections such as brightness and contrast adjustments, quantization, or conversion to a different color space
- Registration (or alignment) of two or more images
- Combination of two or more images, e.g. into an average, blend, difference, or image composite
- Interpolation, demosaicing, and recovery of a full image from a RAW image format like a Bayer filter pattern
- Segmentation of the image into regions
- Image editing and digital retouching
- Extending dynamic range by combining differently exposed images (generalized signal averaging of Wyckoff sets)
and many more.
Besides static two-dimensional images, the field also covers the processing of time-varying signals such as video and the output of tomographic equipment. Some techniques, such as morphological image processing, are specific to binary or grayscale images.
- Photography and printing
- Satellite image processing
- Medical image processing
- Face detection, feature detection, face identification
- Microscope image processing
- Car barrier detection
- Feature extraction
- Pattern recognition
- Multi-scale signal analysis
- Principal components analysis
- Independent component analysis
- Self organizing map
- Hidden Markov model
- Neural networks
- Fuzzy logic
- Digital image editing
- Digital image processing
- Computer graphics
- 2D computer graphics
- Computer vision
- Photo manipulation
- image differencing
- image stabilization
- matte (filmmaking)
- standard test image
- Matrix Vision
- Fundamentals of Image Processing by Ian T. Young, Jan J. Gerbrands, Lucas J. Van Vliet, Paperback, ISBN 90-75691-01-7 (1995)
- Image Analysis and Mathematical Morphology by Jean Serra, ISBN 0-12-637242-3 (1982)
- Image Analysis and Mathematical Morphology, Volume 2: Theoretical Advances by Jean Serra, ISBN 0-12-637241-1 (1988)
- Front-End Vision and Multi-Scale Image Analysis by Bart M. ter Haar Romeny, Paperback, ISBN 1-4020-1507-0 (2003)
- Geometry-Driven Diffusion in Computer Vision by Bart M. ter Haar Romeny (Ed.), ISBN 0-7293-3087-0 (1994)
- Digital Image Processing by Rafael C. Gonzalez, Richard E. Woods, ISBN 0-201-50803-6 (1992)
- Digital Image Processing by William K. Pratt, Paperback, ISBN 0-471-01888-0 (1978)
- National Instruments Vision - Tools for Machine Vision Acquisition and Image Processing
- VIPBase: A collection of utilities for Video and Image Processing
- Tutorial for image processing
- Hypermedia Image Processing Reference
- Fuzzy Image Processing
- Image Processing Jobs
- EMVA - European Machine Vision Association
- Wikia has a wiki about: Computer Vision
- The HALCON library for machine vision
- FILTERS : a free open source image processing library
- RoboRealm - Free Vision Software
- CImg - C++ template image processing library
- mvIMPACT - image processing library
- ADISL's Image Apprentice - Probably the world's most basic C++ based Image Processing Learner's Toolkit
- Free program - numerous filters and pattern making
- Matrox Imaging Library (MIL) - Field-proven software development toolkit for machine vision, medical imaging, and image analysis.
- Machine Vision Industrielle : LiveLiner First Very Simple Imaging Library
- Cantata A Data Flow Visual Language for image processing.