This document provides an overview of image processing. It defines analog and digital images and discusses common file formats like JPEG, PNG, BMP and GIF. Image processing involves performing operations on images to extract useful information or enhance the image. There are three levels of image processing - low level focuses on preprocessing, middle level extracts attributes, and high level analyzes attributes. Applications include digitization, enhancement, restoration, segmentation, recognition and more across fields like medicine, law enforcement, human-computer interfaces and steganography. In conclusion, image processing has broad applications in science and technology due to the growing importance of scientific visualization.

1. IMAGE PROCESSING
Presentation By:
Bibus Poudel
MCA, 1st Semester
Kantipur City College
(KCC)

2. IMAGE
An artifact that depicts visual perception
Practically, every scene around us involves images or image processing
Two dimensional signal, analog or digital, containing intensity or color information arranged along
x and y spatial axis
Two types of images:
• Analog
• Digital
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3. ANALOG IMAGE
Two dimensional function of f(x,y) considered in the continuous time domain
X, Y and the amplitude values of ‘f’ are continuous quantities
Required for human viewing
Examples: photographs, paintings, TV images, medical images
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4. DIGITAL IMAGE
Two dimensional function f(x,y) where x and y are spatial coordinates
X, Y and amplitude values of ‘f’ are all finite and discrete quantities
Made of picture elements called pixels, arranged in an ordered rectangular array
Value of (x,y) at any point gives the pixel value at that point of an image
Dimensions of the pixel array determines the size of image
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5. COMMON IMAGE FILE
FORMATS
JPEG
 Photographic Image
 Image artifacts visible at sharp boundaries
PNG
 Lossless compression
 Format allows to store at different bit depths
BMP
 Almost Raw Format
 32 bit, 24 bit, 16 bit, 15 bit, 8 bit, Indexed (8 bit)
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GIF
 An 8-bit (256 color), non-destructively compressed
bitmap format
 Mostly used for web
Vector Formats
 Contain instructions for drawing
 Need to be rasterized before image processing

6. IMAGE PROCESSING
Method of performing some operations on an image to get enhanced image or extract
some useful information from it
Application of signal processing techniques in the domain of images
Input may be an image, a series of images or a video
Output may be an image or a set of characteristics or understanding related to image
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7. IMAGE PROCESSING: STEPS
INVOLVED
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8. LEVELS OF IMAGE
PROCESSING
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Low Level
• Input: Image
• Output: Image
• Example:
• Image pre-processing to
reduce noise
• Contrast enhancement
• Image sharpening
Middle Level
• Input: Image
• Output: Attributes
extracted from image
• Example:
• Image segmentation
High Level
• Input: Generally attributes
extracted from images
• Output: Image
• Example:
• Image analysis
• Recognize objects in image

9. DIGITAL IMAGE PROCESSING
Processing of digital image using a digital device (computer)
Rapidly growing technology
Major applications:
oImprovement of pictorial information for human interpretation
oProcessing of image data for machine perception such as image analysis, image recognition
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10. ORIGIN OF DIGITAL IMAGE
PROCESSING
One of the first applications of digital images was in the newspaper industry
Introduction of the Bartlane cable picture transmission system in the early 1920s
Used to transmit newspaper images across the Atlantic
True image processing began in 1960s
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11. FIRST DIGITAL IMAGE
First digital photo came in 1957
Russell Kirsch (scientist at the National Bureau of
Standards) made a 176x176 pixel digital image using an
image scanner
Low resolution due to the limitation of computer memory
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12. WHY DIGITAL IMAGE
PROCESSING?
Improve visual quality of image for easier interpretation such as enhancement,
restoration
Process images and extract information from them for machine perception such as
image analysis, image recognition
Perform different operations on image
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13. APPLICATIONS OF DIGITAL
IMAGE PROCESSING
Digitizing an image
• Converting a continuous image to digital
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Enhancing an image
• Modifying image for better application

14. APPLICATIONS OF DIGITAL
IMAGE PROCESSING
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Restoring an image
• Recover a damaged image
Image segmentation
• Partition objects in image from background

15. APPLICATIONS OF DIGITAL
IMAGE PROCESSING
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Compressing an image
• Store with less bytes
Image recognition
• Identify objects in image
• Detecting text in still images
Geographic
Information Systems

16. APPLICATIONS OF DIGITAL
IMAGE PROCESSING
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Artistic Effect In Medicine
Original MRI Image of a Dog Heart Image from Edge Detection

17. APPLICATIONS OF DIGITAL
IMAGE PROCESSING
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Law enforcement
 Number plate recognition
 Fingerprint recognition
 Enhancement of CCTV images

18. APPLICATIONS OF DIGITAL
IMAGE PROCESSING
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Image Steganography
• Hiding data (text, image or other data) within image
• Prevent unintended user from the detection of the hidden messages or data

19. APPLICATIONS OF DIGITAL
IMAGE PROCESSING
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Human Computer Interfaces
 Face Recognition
 Gesture Recognition

20. CONCLUSION
Image and image processing has broad scope in modern sciences and technologies
Growing importance of scientific visualization
Wide range of applications
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21. REFERENCES
•https://sisu.ut.ee/imageprocessing/book/1
•http://cpsc.ualr.edu/milanova/image_processing/
•https://en.wikipedia.org/wiki/
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