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CIS 595 Image Fundamentals

CIS 595 Image Fundamentals. Dr. Rolf Lakaemper. Fundamentals. Parts of these slides base on the textbook Digital Image Processing by Gonzales/Woods Chapters 1 / 2. Fundamentals. These slides show basic concepts about digital images. Fundamentals. In the beginning…

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CIS 595 Image Fundamentals

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  1. CIS 595 Image Fundamentals Dr. Rolf Lakaemper

  2. Fundamentals Parts of these slides base on the textbook Digital Image Processing by Gonzales/Woods Chapters 1 / 2

  3. Fundamentals These slides show basic concepts about digital images

  4. Fundamentals In the beginning… we’ll have a look at the human eye

  5. Fundamentals

  6. Fundamentals • We are mostly interested in the retina: • consists of cones and rods • Cones • color receptors • About 7 million, primarily in the retina’s central portion • for image details • Rods • Sensitive to illumination, not involved in color vision • About 130 million, all over the retina • General, overall view

  7. Fundamentals Distribution of cones and rods:

  8. Fundamentals The human eye is sensible to electromagnetic waves in the ‘visible spectrum’ :

  9. Fundamentals The human eye is sensible to electromagnetic waves in the ‘visible spectrum’ , which is around a wavelength of 0.000001 m = 0.001 mm

  10. Fundamentals • The human eye • Is able to perceive electromagnetic waves in a certain spectrum • Is able to distinguish between wavelengths in this spectrum (colors) • Has a higher density of receptors in the center • Maps our 3D reality to a 2 dimensional image !

  11. Fundamentals …or more precise: maps our continous (?) reality to a (spatially) DISCRETE 2D image

  12. Fundamentals • Some topics we have to deal with: • Sharpness • Brightness • Processing of perceived visual information

  13. Fundamentals Sharpness The eye is able to deal with sharpness in different distances

  14. Fundamentals Brightness The eye is able to adapt to different ranges of brightness

  15. Fundamentals Processing of perceived information: optical illusions

  16. Fundamentals optical illusions: Digital Image Processing does NOT (primarily) deal with cognitive aspects of the perceived image !

  17. Fundamentals What is an image ?

  18. Fundamentals The retinal model is mathematically hard to handle (e.g. neighborhood ?)

  19. Fundamentals Easier: 2D array of cells, modelling the cones/rods Each cell contains a numerical value (e.g. between 0-255)

  20. Fundamentals • The position of each cell defines the position of the receptor • The numerical value of the cell represents the illumination received by the receptor 5 7 1 0 12 4 … … …

  21. Fundamentals • With this model, we can create GRAYVALUE images • Value = 0: BLACK (no illumination / energy) • Value = 255: White (max. illumination / energy)

  22. Fundamentals A 2D grayvalue - image is a 2D -> 1D function, v = f(x,y)

  23. Fundamentals As we have a function, we can apply operators to this function, e.g. H(f(x,y)) = f(x,y) / 2 Operator Image (= function !)

  24. Fundamentals H(f(x,y)) = f(x,y) / 2 6 8 2 0 3 4 1 0 12 200 20 10 6 100 10 5

  25. Fundamentals Remember: the value of the cells is the illumination (or brightness) 6 8 2 0 3 4 1 0 12 200 20 10 6 100 10 5

  26. Fundamentals As we have a function, we can apply operators to this function… …but why should we ? some motivation for (digital) image processing

  27. Fundamentals • Transmission of images

  28. Fundamentals • Image Enhancement

  29. Fundamentals • Image Analysis / Recognition

  30. Fundamentals The mandatory steps: Image Acquisition and Representation

  31. Fundamentals Acquisition

  32. Fundamentals Acquisition

  33. Fundamentals Acquisition

  34. Fundamentals • Typical sensor for images: • CCD Array (Charge Couple Devices) • Use in digital cameras • Typical resolution 1024 x 768 (webcam)

  35. Fundamentals CCD

  36. Fundamentals CCD

  37. Fundamentals CCD: 3.2 million pixels !

  38. Fundamentals Representation The Braun Tube

  39. Fundamentals Representation Black/White and Color

  40. Fundamentals Color Representation: Red / Green / Blue Model for Color-tube Note: RGB is not the ONLY color-model, in fact its use is quiet restricted. More about that later.

  41. Fundamentals Color images can be represented by 3D Arrays (e.g. 320 x 240 x 3)

  42. Fundamentals But for the time being we’ll handle 2D grayvalue images

  43. Fundamentals Digital vs. Analogue Images Analogue: Function v = f(x,y): v,x,y are REAL Digital: Function v = f(x,y): v,x,y are INTEGER

  44. Fundamentals Stepping down from REALity to INTEGER coordinates x,y: Sampling

  45. Fundamentals Stepping down from REALity to INTEGER grayvalues v : Quantization

  46. Fundamentals Sampling and Quantization

  47. Fundamentals MATLAB demonstrations of sampling and quantization effects

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