Image processing - An Overview
Updated: Aug 23, 2020
We would have witnessed the high-resolution photographs in many wedding albums or in the albums of house warming functions. In social media, we would have seen many images of celebrities. Have you ever wonder, how these clear-cut images are being made? All these images are the end product of a process named Image processing. It is a method to perform some operations on an image, in order to get an enhanced image or to extract some useful information from it.
Image analysts use various fundamentals of interpretation while performing #imageprocessing. In this article, we are going to see in detail the types of image processing, its applications, and the future of it.
The term #image can be defined as an artifact that can provide visual perception such as a photograph or other two-dimensional picture of any physical object. They can be captured by optical devices such as cameras, lenses, telescopes, and even microscopes.
Image processing is a type of signal processing in which input is an image and output may be an image or characteristic associated with that image. It is one of the rapidly growing #technologies. The process of image processing mainly includes three steps. They are,
Importing the image via image acquisition tools.
Analyzing and manipulating the image.
Output in which the result can be an altered image or the report based on the image analysis.
Image processing can be divided into analog and digital image processing.
Analog Image Processing:
If the pictorial representation of the data is done in analog wave formats, then it can be called as an analog image. The process of improvising the image further is called as the analog image processing. Example: Processing of hard copies like printouts and #photographs. Also, television broadcasting is done in the older days with the help of analog dish antennas.
But as technology gets improved over the period, analog processing is replaced by digital image processing because of its various disadvantages. The primary disadvantage is the analog signals are more prone to noise. This unwanted noise results in signal loss and distortion. The error caused in this way is difficult to rectify, since amplifying the signal to recover the attenuated parts of the signal also amplifies the noise.
Even if the resolution of the signal is improved, the difference can be overshadowed by the noise in the signal. As a result of all these, the credibility of analog image processing becomes questionable. So, it is replaced by digital image processing.
Digital Image Processing:
This type of image processing technique helps in manipulating the digital image with the help of computers. The four common phases that all kinds of data should undergo while using digital techniques are preprocessing, enhancement, information extraction, and display. It allows a wider range of algorithms to be applied to the input data and can avoid the build-up of noise and distortions during the processing. Example: All forms of computer #graphics, digital photography.
The generation and development of digital image processing are influenced by three factors namely the development of computers, improvement of discrete mathematics theory, and a wide range of applications in the environment such as agriculture, medical science, and military defense.
Characteristics of Digital Image Processing:
Open source, as well as the licensed software, such as Matlab, Adobe #Photoshop are employed in the process of image processing.
It also does image enhancement to recollect the data through images.
We can perform several operations such as zooming, blurring, image recognition, image retrieval, greyscale conversion, and edges detecting.
Fast and high-quality image distribution can be achieved with the help of digital image processing.
A wide range of data acquisition can be attained with the help of digital radiography, CT.
Analysis of digital images can be performed with the help of computer-aided diagnosis, and by calculating various other parameters.
In image processing, anisotropic diffusion is employed. It is a technique to reduce the image noise without removing edges, lines, or other details required to interpret an image.
Applications of Digital Image processing:
Digital image processing is not limited just to adjust the spatial resolution of the images captured by a camera and to increase the brightness of the photo. Other than these, it has very wide applications and almost all the technical fields are impacted by digital image processing.
The common applications in the field of medical science include gamma-ray imaging, Positron Emission Tomography (PET) scan, CT scan, Ultraviolet, and X-ray imaging.
In the field of remote sensing, digital image processing is employed to detect infrastructure damages caused by earthquakes.
The presence of resources like petroleum, granites can be detected by processing the image captured by the satellites. It is done by the extraction of edges, and by the enhancement of various types of edges.
It also helps in transmitting and encoding the images over a long distance. Different formats have been developed for high or low bandwidth to encode the photos and stream them over the internet.
In robotics, image processing is applied to complete various tasks such as hurdle detection, line following.
Color processing is one of the major applications of digital image processing. It involves the study of different color spaces and the encoding of colored images. Example: YCbCr, HSV, and RGB color model.
In pattern recognition, image processing is used for identifying the objects in an image and then the machine learning is used to train the system for the change in pattern.
Video processing is also done with the help of this. A video is nothing but a very fast movement of the pictures. Video processing involves motion detection, frame rate conversion, color space conversion, aspect ratio conversion.
Future of Image processing:
Due to the various advancements in the field of science and technology, image processing has now become an integral part of Artificial Intelligence (#AI) systems. New types of processing systems are being introduced in chemical, thermal, and molecular imaging.
Image processing has led to tremendous growth in the field of space exploration. Most new satellites use different kinds of sensors to collect information from outer space. Stars and galaxies which are located at a distance of several light-years can be pictured with the help of advanced image processing technology.
In this modern era of science, all our day to day activities is being automated. A computer vision-based text scanner can be implemented with the help of an optical character recognition algorithm. We can also operate the computer mouse by our vision. The advanced security system is now being developed by using the concept of face lock. The facial feature recognition algorithm along with image processing concepts is applied for this system.
The robustness of any evolved architecture to its intrinsic and autonomous restructuring of electric circuits can be identified and rectified with the help of image processing.