Introduction to Digital Image Processing

Introduction to digital image processing

1. DIGITAL IMAGE PROCESSING The Introduction

2. What is an Image? An image may be defined as a two-dimensional function f(x, y), where x and y are spatial (plane) coordinates, and the amplitude of f at any pair of coordinates (x, y) is called the intensity or gray level of the image at that point. An image is a pictorial representation of objects under perception

3. Image A 2D function, f(x, y) x and y are spatial coordinates Amplitude of f is called the intensity or gray level

4. What is Digital Image? Definition 1: If (x, y) and the amplitude values of f are finite and discrete quantities, we call the image a digital image. A digital image is composed of a finite number of elements called pixels, each of which has a particular location and value. Definition 2: A digital image is a representation of a two-dimensional image as a finite set of digital values, called picture elements or pixels.

5. Digital image x, y, f(x, y) are all finite and discrete is composed of a finite number of elements These elements are referred to as picture elements image elements Pels pixels - most widely used

6. Common image formats include: 1 sample per point (B&W or Grayscale) 3 samples per point (Red, Green, and Blue)

7. Digital image processing Processing of digital images on a digital computer Digital image processing focuses on two major tasks Improvement of pictorial information for human interpretation Processing of image data for storage, transmission and representation for autonomous machine perception

8. Contd. DIP The continuum from image processing to computer vision can be broken up into low-, mid- and high-level processes.

9. Light and the Electromagnetic Spectrum Sir Isaac Newton discovered that when a beam of sunlight is passed through a glass prism, The emerging beam of light is not white but consists of a continuous spectrum of colors ranging from violet at one end to red at the other.

10. Light is a particular type of electromagnetic radiation that can be seen and sensed by the human eye. The visible band of the electromagnetic spectrum spans the range from approximately 0.43 m (violet) to about 0.79 m (red). The colors that humans perceive in an object are determined by the nature of the light reflected from the object.

11. The electromagnetic spectrum can be expressed in terms of wavelength, frequency, or energy. Wavelength ( λ ) and frequency ( γ ) are related by the expression λ =c / γ where c is the speed of light (2.998*108ms) The energy of the electromagnetic spectrum is given by the expression E=h . γ where h is Planck’s constant

12. Images from Different EM Radiation Radio waves - Radar imaging , Magnetic Resonance Imaging (MRI) Microwave - Microwave imaging Infrared Rays- Infrared imaging, Thermal Imaging Visible Spectrum- Photographs UV Rays- Ultraviolet imaging telescopes X‐rays - X‐rays and Computed tomography (CT Scan) Gamma rays - Positron emission tomography (PET Scan) Ultrasound (not EM waves)

13. Gamma Ray Imaging Nuclear Medicine Astronomical Observations

14. X-ray Imaging Examples of X-ray imaging. Chest X-ray. Aortic angiogram. Head CT. Circuit boards. Cygnus Loop.

15. Imaging in the Ultraviolet Band Applications: Lithography Industrial Inspection Microscopy Lasers Biological imaging Astronomical observations. (a) shows a fluorescence microscope image of normal corn, (b) shows corn infected by “smut,” a disease of cereals, corn… (c) Shows the Cygnus Loop imaged in the high-energy region of the ultraviolet band.

16. Imaging in the Visible Bands Artistic effects are used to make images more visually appealing, to add special effects and to make composite images

17. Examples: Law Enforcement Image processing techniques are used extensively by law enforcers Number plate recognition for speed cameras/automated toll systems Fingerprint recognition Enhancement of CCTV images

18. Infrared band imaging

19. Examples: GIS Geographic Information Systems Digital image processing techniques are used extensively to manipulate satellite imagery Terrain classification Meteorology

20. Examples: GIS (cont…) Night-Time Lights of the World data set Global inventory of human settlement Not hard to imagine the kind of analysis that might be done using this data

21. Radio band imaging- Medical field

22. Key Stages in Digital Image Processing Image Acquisition Image Restoration Morphological Processing Segmentation Representation & Description Image Enhancement Object Recognition Problem Domain Colour Image Processing Image Compression

23. Key Stages in Digital Image Processing: Image Aquisition Image Acquisition Image Restoration Morphological Processing Segmentation Representation & Description Image Enhancement Object Recognition Problem Domain Colour Image Processing Image Compression

24. Key Stages in Digital Image Processing: Image Enhancement Image Acquisition Image Restoration Morphological Processing Segmentation Representation & Description Image Enhancement Object Recognition Problem Domain Colour Image Processing Image Compression Images taken from Gonzalez & Woods, Digital Image Processing (2002)

25. Key Stages in Digital Image Processing: Image Restoration Image Acquisition Image Restoration Morphological Processing Segmentation Representation & Description Image Enhancement Object Recognition Problem Domain Colour Image Processing Image Compression Images taken from Gonzalez & Woods, Digital Image Processing (2002)

26. Key Stages in Digital Image Processing: Morphological Processing Image Acquisition Image Restoration Morphological Processing Segmentation Representation & Description Image Enhancement Object Recognition Problem Domain Colour Image Processing Image Compression Images taken from Gonzalez & Woods, Digital Image Processing (2002)

27. Key Stages in Digital Image Processing: Segmentation Image Acquisition Image Restoration Morphological Processing Segmentation Representation & Description Image Enhancement Object Recognition Problem Domain Colour Image Processing Image Compression Images taken from Gonzalez & Woods, Digital Image Processing (2002)

28. Key Stages in Digital Image Processing: Object Recognition Image Acquisition Image Restoration Morphological Processing Segmentation Representation & Description Image Enhancement Object Recognition Problem Domain Colour Image Processing Image Compression Images taken from Gonzalez & Woods, Digital Image Processing (2002)

29. Key Stages in Digital Image Processing: Representation & Description Image Acquisition Image Restoration Morphological Processing Segmentation Representation & Description Image Enhancement Object Recognition Problem Domain Colour Image Processing Image Compression Images taken from Gonzalez & Woods, Digital Image Processing (2002)

30. Key Stages in Digital Image Processing: Image Compression Image Acquisition Image Restoration Morphological Processing Segmentation Representation & Description Image Enhancement Object Recognition Problem Domain Colour Image Processing Image Compression

31. Key Stages in Digital Image Processing: Colour Image Processing Image Acquisition Image Restoration Morphological Processing Segmentation Representation & Description Image Enhancement Object Recognition Problem Domain Colour Image Processing Image Compression

32. Components of DIP