Fundamental steps in digital image processing
The different tasks being done in DIP are divided into two broad categories based on the output of the study and all the DIP methods or techniques must have output of any of the shapes amongst the two categories the categories are.
- Input is an image and the output is also an image.
- Input is the image and output is the attribute extracted from an image.
Below is the graphical notation for the fundamental steps in image processing
Image acquisition is the processing of acquiring an image; it deals with the origin of the image and different preprocessing steps, like scaling.
Image filtering and enhancement is when the captured image is being enhanced (improving quality) using different methods like filtering an image or any other enhancement operations. Image enhancement is subjective as it depends on the specific type of task and specific data. For the X-ray image, you may need image filtering but on a satellite image, you may not need it.
Image restoration is again the step of improving the quality of an image but unlike image enhancement which is task-specific and depends on the owner or person who is the decision maker here the decision is based on mathematical relations and probabilities. Image restoration is objective.
Color image processing is the most popular subfield of DIP nowadays because of the amount of quality of color images produced each day by humans and consumed by humans before bow we have worked with grey images but now onward we will work on color where we have three channels instead of just one and we will know how to apply a different operation on color images.
Wavelets transform based on the concept of representing images in different resolutions to perform different kinds of tasks which is not possible in the original form.
Compression is the technique of reducing the size of digital images nowadays this technique may not be helpful for storing images as we have no issues with space but it may be helpful on the internet to transfer the data where the bandwidth matters.
Morphological processing deals with the tools used to extract image components that are useful in describing and representing the shape of the object in the image
Segmentation is the task of separating the region of interest in the given image; it can be done using different classical algorithms and advanced deep-learning architectures.
Feature extraction follows the output of the segmentation where the boundary or the edges of the object are extracted. Feature extraction consists of two parts feature detection and feature description. Feature detection refers to the detection of the boundary of the object in the image and feature description refers to the quantitative description of the detected features.
Image classification follows the output of the feature extraction step where the label is given to the extracted feature of the object in the image. E.g. car, bike etc.
Component required for DIP system
To perform DIP on images or even videos we need a special type of system that has all the capabilities to handle the task of DIP because here we work with images and it could be costly or even impossible for most of the systems that we have it requires specialized hardware software and computers to perform DIP operation so we need to have that system before going into the DIP. The components of a DIP system are Image sensors, Specialized image process hardware, Specialized software, computer, Mass storage, Image display, Hardcopy, and Network communication.
To sense or capture an image the sensors must have two components these are the physical device which is used to read or sense the radiation emitted by the object and the second component is the digitizer which is used to quantize and digitize the continuous signals into discrete values.
To process the image we need specialized processing hardware that has to have two components that is the digitizer and ALU to perform arithmetic and logical operations on the image.
To interact with this hardware we need special software for image processing where we can write high-level instructions to be performed by the hardware on the image.
After processing we will be required to store the process image somewhere for that we need a Mass storage device because these images require more space to be stored but today it is not an issue.
For storing 1024*1024 resolution pixel each pixel need 8 byte space require 1MB space for the image.
To view the image we need a high-level display to look at the effect on an image after preprocessing and before preprocessing and the image affects our required task.
And also we need sometime a hard copy in the form of a CD player to store the image. But nowadays we have the internet to transfer data/images usually we do not need the hard copy.
The below image shows the Components of the DIP system