- DIP - Computer Vision and Graphics
- DIP - Optical Character Recognition
- DIP - JPEG compression
- DIP - Introduction to Color Spaces
- DIP - High Pass vs Low Pass Filters
- DIP - Convolution theorm
- DIP - Fourier series and Transform
- DIP - Frequency Domain Analysis
- DIP - Laplacian Operator
- DIP - Krisch Compass Mask
- DIP - Robinson Compass Mask
- DIP - Sobel operator
- DIP - Prewitt Operator
- DIP - Concept of Edge Detection
- DIP - Concept of Blurring
- DIP - Concept of Masks
- DIP - Concept of convolution
- DIP - Gray Level Transformations
- DIP - Histogram Equalization
- DIP - Introduction to Probability
- DIP - Histogram Stretching
- DIP - Histogram Sliding
- DIP - Image Transformations
- DIP - Brightness and Contrast
- DIP - Histograms Introduction
- DIP - Concept of Dithering
- DIP - ISO Preference curves
- DIP - Concept of Quantization
- DIP - Gray Level Resolution
- DIP - Pixels Dots and Lines per inch
- DIP - Spatial Resolution
- DIP - Zooming methods
- DIP - Concept of Zooming
- DIP - Pixel Resolution
- DIP - Concept of Sampling
- DIP - Grayscale to RGB Conversion
- DIP - Color Codes Conversion
- DIP - Types of Images
- DIP - Concept of Bits Per Pixel
- DIP - Perspective Transformation
- DIP - Concept of Pixel
- DIP - Camera Mechanism
- DIP - Image Formation on Camera
- DIP - Concept of Dimensions
- DIP - Applications and Usage
- DIP - History of Photography
- DIP - Signal and System Introduction
- DIP - Image Processing Introduction
- DIP - Home
DIP Useful Resources
Selected Reading
- Who is Who
- Computer Glossary
- HR Interview Questions
- Effective Resume Writing
- Questions and Answers
- UPSC IAS Exams Notes
Apppcations and Usage
Since digital image processing has very wide apppcations and almost all of the technical fields are impacted by DIP, we will just discuss some of the major apppcations of DIP.
Digital Image processing is not just pmited to adjust the spatial resolution of the everyday images captured by the camera. It is not just pmited to increase the brightness of the photo, e.t.c. Rather it is far more than that.
Electromagnetic waves can be thought of as stream of particles, where each particle is moving with the speed of pght. Each particle contains a bundle of energy. This bundle of energy is called a photon.
The electromagnetic spectrum according to the energy of photon is shown below.
![Electro Magnetic spectrum](/dip/images/electro_spectrum.jpg)
In this electromagnetic spectrum, we are only able to see the visible spectrum.Visible spectrum mainly includes seven different colors that are commonly term as (VIBGOYR). VIBGOYR stands for violet , indigo , blue , green , orange , yellow and Red.
But that doesnot nulpfy the existence of other stuff in the spectrum. Our human eye can only see the visible portion, in which we saw all the objects. But a camera can see the other things that a naked eye is unable to see. For example: x rays , gamma rays , e.t.c. Hence the analysis of all that stuff too is done in digital image processing.
This discussion leads to another question which is
why do we need to analyze all that other stuff in EM spectrum too?
The answer to this question pes in the fact, because that other stuff such as XRay has been widely used in the field of medical. The analysis of Gamma ray is necessary because it is used widely in nuclear medicine and astronomical observation. Same goes with the rest of the things in EM spectrum.
Apppcations of Digital Image Processing
Some of the major fields in which digital image processing is widely used are mentioned below
Image sharpening and restoration
Medical field
Remote sensing
Transmission and encoding
Machine/Robot vision
Color processing
Pattern recognition
Video processing
Microscopic Imaging
Others
Image sharpening and restoration
Image sharpening and restoration refers here to process images that have been captured from the modern camera to make them a better image or to manipulate those images in way to achieve desired result. It refers to do what Photoshop usually does.
This includes Zooming, blurring , sharpening , gray scale to color conversion, detecting edges and vice versa , Image retrieval and Image recognition. The common examples are:
The original image
![Einstein](/dip/images/einstein_1.jpg)
The zoomed image
![Einstein](/dip/images/einstein_zoomed.jpg)
Blurr image
![Blur](/dip/images/blur.jpg)
Sharp image
![Sharp](/dip/images/sharp.jpg)
Edges
![edges](/dip/images/edges.jpg)
Medical field
The common apppcations of DIP in the field of medical is
Gamma ray imaging
PET scan
X Ray Imaging
Medical CT
UV imaging
UV imaging
In the field of remote sensing , the area of the earth is scanned by a satelpte or from a very high ground and then it is analyzed to obtain information about it. One particular apppcation of digital image processing in the field of remote sensing is to detect infrastructure damages caused by an earthquake.
As it takes longer time to grasp damage, even if serious damages are focused on. Since the area effected by the earthquake is sometimes so wide , that it not possible to examine it with human eye in order to estimate damages. Even if it is , then it is very hectic and time consuming procedure. So a solution to this is found in digital image processing. An image of the effected area is captured from the above ground and then it is analyzed to detect the various types of damage done by the earthquake.
![Remote sensing](/dip/images/remote_sensing.jpg)
The key steps include in the analysis are
The extraction of edges
Analysis and enhancement of various types of edges
Transmission and encoding
The very first image that has been transmitted over the wire was from London to New York via a submarine cable. The picture that was sent is shown below.
![transmission](/dip/images/transmission.jpg)
The picture that was sent took three hours to reach from one place to another.
Now just imagine , that today we are able to see pve video feed , or pve cctv footage from one continent to another with just a delay of seconds. It means that a lot of work has been done in this field too. This field doesnot only focus on transmission , but also on encoding. Many different formats have been developed for high or low bandwith to encode photos and then stream it over the internet or e.t.c.
Machine/Robot vision
Apart form the many challenges that a robot face today , one of the biggest challenge still is to increase the vision of the robot. Make robot able to see things , identify them , identify the hurdles e.t.c. Much work has been contributed by this field and a complete other field of computer vision has been introduced to work on it.
Hurdle detection
Hurdle detection is one of the common task that has been done through image processing, by identifying different type of objects in the image and then calculating the distance between robot and hurdles.
![Hurdle detection](/dip/images/hurdle_detection.jpg)
Line follower robot
Most of the robots today work by following the pne and thus are called pne follower robots. This help a robot to move on its path and perform some tasks. This has also been achieved through image processing.
![Robot](/dip/images/pne_follow.jpg)
Color processing
Color processing includes processing of colored images and different color spaces that are used. For example RGB color model , YCbCr, HSV. It also involves studying transmission , storage , and encoding of these color images.
Pattern recognition
Pattern recognition involves study from image processing and from various other fields that includes machine learning ( a branch of artificial intelpgence). In pattern recognition , image processing is used for identifying the objects in an images and then machine learning is used to train the system for the change in pattern. Pattern recognition is used in computer aided diagnosis , recognition of handwriting , recognition of images e.t.c
Video processing
A video is nothing but just the very fast movement of pictures. The quapty of the video depends on the number of frames/pictures per minute and the quapty of each frame being used. Video processing involves noise reduction , detail enhancement , motion detection , frame rate conversion , aspect ratio conversion , color space conversion e.t.c.
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