Image Processing
Introduction
Image processing is a subfield of signal processing where the input is an image and the output can either be an image or a set of characteristics or parameters related to the image. It involves performing operations on images to enhance their quality or to extract useful information from them.
History
The history of image processing dates back to the 1920s when the first image processing techniques were used in the newspaper industry. The use of image processing has grown significantly with the development of computer technology. Today, image processing techniques are used in a wide range of applications, from medical imaging to remote sensing and beyond.
Types of Image Processing
There are two types of image processing – Analog and Digital Image Processing. Analog image processing can be used for the hard copies like printouts and photographs. Digital techniques are used to manipulate the digital images by using computers.
Analog Image Processing
Analog image processing is done on analog signals. It includes processes like the alteration of brightness, contrast and the intensity level of the image.
Digital Image Processing
Digital image processing focuses on two major tasks –Improvement of pictorial information for human interpretation and processing of image data for storage, transmission and representation for autonomous machine perception.
Techniques of Image Processing
There are several techniques used in the process of image processing, including:
Image Enhancement
Image enhancement is among the simplest and most appealing areas of digital image processing. Basically, the idea behind enhancement techniques is to bring out detail that is obscured, or simply to highlight certain features of interest in an image.
Image Restoration
Image restoration is an area that also deals with improving the appearance of an image. However, unlike enhancement, which is subjective, image restoration is objective, in the sense that restoration techniques tend to be based on mathematical or probabilistic models of image degradation.
Color Image Processing
Color image processing is an area that has been gaining its importance because of the significant increase in the use of digital images on the Internet.
Wavelets and Multi-resolution Processing
Wavelets are the foundation for representing images in various degrees of detail. Applications that use multi-resolution representations are far ranging, and include image compression, pyramidal representation, where an image is subsampled successively to produce a sequence of reduced resolution images, and more.
Image Compression
Image compression addresses the problem of reducing the amount of data required to represent a digital image. The underlying basis of the reduction process is the removal of redundant data.
Morphological Processing
Morphological processing deals with tools for extracting image components that are useful in the representation and description of shape.
Applications of Image Processing
Image processing has been an important stream of Research for various fields. Some of the application areas of Image processing are listed below:
Image sharpening and restoration
Image sharpening and restoration helps to create a better image by increasing the contrast or by removing the blur.
Medical field
Image processing plays a vital role in the medical field for image representation (to visualize the body parts and functions), diagnosis (to identify diseases) and treatment (to perform surgeries).
Remote sensing
In remote sensing, image processing is used to create earth maps, weather maps, etc.
Face detection, recognition and identification
Image processing is used for face detection and recognition. It is used in biometrics, security systems, and surveillance systems.
Industrial inspection
Image processing is used in industrial inspection to find defects in a product.
Conclusion
Image processing has a wide array of applications, from medical diagnostics to industrial quality control and remote sensing. As technology continues to advance, the scope and potential of image processing also continue to expand.
See Also
