Fundamental Steps of Digital Image Processing
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In this article, we are going to learn some fundamentals of Image Processing which is quite often used in Computer Vision problems. We will understand how various processing techniques affect an image and what is the aftermath of the resultant image by applying those processing algorithms.
There are two types of methods used for image processing namely, analog and digital image processing.
- Analog image processing can be used for hard copies like printouts and photographs.
- Digital image processing techniques help in the manipulation of digital images by using computers.
What is an image?
- A two-dimensional array of numbers(or pixels) ranging between 0 and 255.
- It is defined by the mathematical function f(x,y) where x and y are the two co-ordinates horizontally and vertically.
The range of the colors in 8 bit vary from 0–255 where:
- 0 — black
- 255 — white
- 127 — gray color.
What is a black and white image?
- The image consists of black and white color only.
What are greyscaled images?
- It is a black and white image, but the name emphasizes that such an image will also include many shades of grey.
- The values ranging between 0 and 255.
Why do we process images?
It has been developed to deal with 3 major problems —
- To improve the image data to suppress the unwanted distortions.
- To enhance some features of the input image.
- As a means of translation between the human visual system and digital imaging devices.
The steps involved in image processing are as follows:
Image Acquisition
- It is basically capturing an image.
- Generally, the image acquisition stage involves pre-processing, such as scaling, etc.
Basic operations on Image
Image Enhancement
- It is the process of filtering image(removing noise, increasing contrast, etc) to improve the quality.
- The resulting image will be more suitable than the original image.
Image Restoration
- It is the process of improving appearance (reducing blurring etc) of an image by mathematical or probabilistic models.
Color Image Processing
- It has become more popular since the use of the digital image has increased.
Multi-Resolution Processing
- It is the process of representing images in various degrees of resolution.
Compression
- It involves the techniques for reducing the size of the image with minimum deterioration in its quality.
Morphological Processing
- It is the process for extracting image components that are useful in the representation and description of shape.
Segmentation
- It is the process of partitioning the image into multiple segments.
Representation and Description
- It involves representing an image in various forms:
- Boundary Representation — It focuses on the external shape characteristics such as corners and inflections.
- Regional Representation — It focuses on internal properties such as texture and skeletal shape.
- Description aka Feature selection helps in extracting useful information.
Feature Matching
- We can extract the same features from a different image of the same cathedral taken from a different angle.
Recognition
- It is the process of assigning labels to an object based on its description.
So, this was an overview of topics in image processing. I hope the outputs helped you visualize well. You can apply these techniques to any image.
These are some fundamental steps but as they are fundamental, all these steps may have sub-steps which will be covered later. Thank you for reading. If you have any thoughts, comments or critics please comment down below.
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There is much more coming…
