Table of Contents
Introduction of Digital Image Processing
Digital image processing is the processing of digital images through algorithms by using a digital computer. These digital computers can make lots of calculation in minimal time.
As a subcategory or discipline of digital signal processing, digital image processing offers many benefits over analog image processing system. This permits a much wider range of algorithms to be applied to the input data, avoiding problems such as noise and distortion buildup during processing. Since images are defined in two dimensions, digital image processing can be modeled as a multidimensional system.
The emergence and development of digital image processing is primarily influenced by the development of mathematics and increasing demand for a wide range of applications in the environmental, agricultural, military, industrial and medical fields.
Fundamental Steps in Digital Image Processing
Various steps in digital image processing are listed below.
- Image Acquisition
- Image Enhancement
- Image Restoration
- Color Image Processing
- Wavelets and Multiresolution Processing
- Image Compression
- Morphological Image Processing
- Image Segmentation
- Image Recognition
We will discuss about these fundamental steps of digital image processing in detail.
1. Image Acquisition
Image acquisition is step one in photo processing. This step is likewise referred to as preprocessing in photo processing. It entails retrieving the photo from a source, typically a hardware-primarily based totally source.
2. Image Enhancement
Image enhancement is the technique of bringing out and highlighting sure functions of hobby in an photo that has been obscured. This can contain converting the brightness, contrast, etc.
3. Image Restoration
Image recuperation is the technique of enhancing the arrival of an photo. However, not like photo enhancement, photo recuperation is carried out the usage of sure mathematical or probabilistic models.
4. Color Image Processing
Color photo processing consists of some of shadeation modeling strategies in a virtual domain. This step has won prominence because of the sizeable use of virtual pix over the internet.
5. Wavelets and Multiresolution Processing
Wavelets are used to symbolize pix in diverse stages of resolution. The pix are subdivided into wavelets or smaller areas for information compression and for pyramidal representation.
6. Image Compression
Compression is a technique used to lessen the garage required to keep an photo or the bandwidth required to transmit it. This is carried out especially while the photo is to be used at the Internet.
7. Morphological Image Processing
Morphological processing is a fixed of processing operations for morphing pix primarily based totally on their shapes.
8. Image Segmentation
Segmentation is one of the maximum tough steps of photo processing. It entails partitioning an photo into its constituent elements or gadgets.
9. Representation and Description
After an photo is segmented into areas withinside the segmentation technique, every place is represented and defined in a shape appropriate for in addition laptop processing. Representation offers with the photo’s traits and local properties. Description offers with extracting quantitative statistics that allows differentiate one magnificence of gadgets from the other.
10. Image Recognition
Recognition assigns a label to an item primarily based on its description.
Applications and Uses of Digital Image Processing
Digital image processing is alive and well in almost every field, growing with new technologies over time.
I have described various uses of digital image processing.
1. Image Sharpening and Restoration
Refers to the process by which the appearance of an image can be changed. It basically manipulates the image to achieve the desired output. This includes transform, sharpen, blur, edge detection, image search, and image detection.
2. Medical
In the medical field there are several applications that rely on digital imaging mechanics, such as gamma imaging, PET scanning, X-ray imaging, medical CT scanning and UV imaging.
3. Robot Vision
There are some robotic machines that work with digital image processing. Robots pave the way through image processing technology, such as hurdle detection route robots and line follower robots.
4. Pattern Recognition
The study of image processing, combined with artificial intelligence, computer-aided diagnosis, handwriting recognition and image recognition can be easily realized. Today image processing is used for pattern recognition.
5. Video processing
It is also one of the applications of digital image processing. Arrange a frame or a collection of images so that you can quickly move between them. Includes frame rate conversion, motion detection, noise reduction, color space conversion, and more.
Pros:
- Image reconstruction (CT, MRI, SPECT, PET).
- image reformatting (multiplane, multiview reconstruction). Fast storage and retrieval of
- images.
- Fast and high quality image delivery.
- Controlled display (windowing, zooming).
Cons:
- Very time consuming.
- Some systems are very expensive.
- Skilled person can easily edit the image.