What is Digital Image Processing?
Digital image processing is the process of using computer algorithms to perform image processing on digital images. Being a subcategory of digital signal processing, digital image processing is better and carries many advantages over analog image processing. It permits to apply multiple algorithms to the input data and does not cause the problems such as the build-up of noise and signal distortion while processing. As images are defined over two or more dimensions that make digital image processing “a model of multidimensional systems”.
Fields of research in Digital Image Processing
1. Image Acquisition:
Image Acquisition is the first and important step of digital image of processing. Its style is very simple just like being given an image which is already in digital form and it involves preprocessing such as scaling etc. It starts with the capturing of image by sensor (such as a monochrome or color TV camera) and digitized. In case, output of the camera or sensor is not in digital form then an analog-to-digital converter (ADC) digitizes it.
2. Image Enhancement:
Image enhancement is one of the easiest and the most important areas of digital image processing. The core idea behind image enhancement is to find out information that is obscured, or to highlight specific features according to the requirements of an image. Such as, changing brightness & contrast etc. Basically, it involves manipulation of an image to get desired image than original for specific applications.
3. Image Restoration:
Image restoration involves improving the appearance of an image. In comparison to image enhancement which is subjective, image restoration is completely objective which makes the sense that restoration techniques are based on probabilistic or mathematical models of image degradation.
4. Color Image Processing:
Color image processing has been proved to be of great interest because of the significant increase in use of digital images on the Internet. It includes color modeling and processing in a digital domain etc.
5. Wavelets and Multi Resolution Processing:
Wavelets act as a base for representing images in varying degrees of resolution. Images subdivision means dividing images into smaller regions for data compression and for pyramidal representation.
Compression involves the techniques that are used for reducing storage necessary to save an image or bandwidth to transmit it. If we talk about its internet usage, it is mostly used to compress data.
7. Morphological Processing:
Morphological processing involves extracting tools of image components which are further used in the representation and description of shape.
Segmentation involves dividing an image into its constituent parts or objects. Generally, autonomous image segmentation is one of the toughest tasks in digital image processing. It is a rugged segmentation procedure that takes a long way toward successful solution of imaging problems that require objects to be identified individually.
9. Representation and Description:
The behavior of representation and description depends on the output of a segmentation stage and it includes raw pixel data, constituting either all the points in the reign or only boundary of the reign. Choosing a representation is a part of solution to transform raw data into a suitable form that allows subsequent computer processing. As description deals with extracting attributes that yield quantitative information of interest or basic to separate one class from another.
10. Object recognition:
Recognition involves assigning of a label, such as, “vehicle” to an object completely based on its descriptors.
11. Knowledge Base:
Knowledge is all about detailing regions of an image to locate the information of interest that ultimately delimits the research to be conducted in seeking that information. Knowledge Base becomes complex such as an interconnected list of all major possible defects in materials assessment problems or an image database carrying high-resolution satellite images of a region in relation with change-detection applications.