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Digital Image Processing

Digital Image Processing. Chapter 2: Digital Image Fundamentals . Elements of Visual Perception. Structure of the human eye. Rods and cones in the retina. Image formation in the eye. Brightness adaptation and discrimination. Brightness discrimination. Weber ratio. Perceived brightness.

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Digital Image Processing

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  1. Digital Image Processing Chapter 2: Digital Image Fundamentals

  2. Elements of Visual Perception • Structure of the human eye

  3. Rods and cones in the retina

  4. Image formation in the eye

  5. Brightness adaptation and discrimination

  6. Brightness discrimination

  7. Weber ratio

  8. Perceived brightness

  9. Simultaneous contrast

  10. Optical illusion

  11. Light and the Electromagnetic Spectrum

  12. Wavelength

  13. Image Sensing and Acquisition

  14. Image acquisition using a single sensor

  15. Using sensor strips

  16. A simple image formation model

  17. Illumination and reflectance • Illumination and transmissivity

  18. Image Sampling and Quantization

  19. Sampling and quantization

  20. Representing digital images

  21. Saturation and noise

  22. Number of storage bits

  23. Spatial and gray-level resolution

  24. Subsampled and resampled

  25. Reducing spatial resolution

  26. Varying the number of gray levels

  27. Varying the number of gray levels

  28. N and k in different-details images

  29. Isopreference

  30. Interpolations

  31. Zooming and shrinking

  32. Some Basic Relationships Between Pixels • Neighbors of a pixel • : 4-neighbors of p , , , : four diagonal neighbors of p , , , : 8-neighbors of p and

  33. Adjacency • : The set of gray-level values used to define adjacency • 4-adjacency: Two pixels p and q with values from V are 4-adjacency if q is in the set • 8-adjacency: Two pixels p and q with values from V are 8-adjacency if q is in the set

  34. m-adjacency (mixed adjacency): Two pixels p and q with values from V are m-adjacency if • q is in , or • q is in and the set has no pixels whose values are from V

  35. Subset adjacency • S1 and S2 are adjacent if some pixel in S1 is adjacent to some pixel in S2 • Path • A path from p with coordinates to pixel q with coordinates is a sequence of distinct pixels with coordinates • , ,…, where = , = , and pixels and are adjacent

  36. Region • We call R a region of the image if R is a connected set • Boundary • The boundary of a region R is the set of pixels in the region that have one or more neighbors that are not in R • Edge • Pixels with derivative values that exceed a preset threshold

  37. Distance measures • Euclidean distance • City-block distance • Chessboard distance

  38. distance: The shortest m-path between the points

  39. An Introduction to the Mathematical Tools Used in Digital Image Processing • Linear operation • H is said to be a linear operator if, for any two images f and g and any two scalars a and b,

  40. Arithmetic operations • Addition

  41. Arithmetic operations • Subtraction

  42. Digital subtraction angiography

  43. Shading correction

  44. Image multiplication

  45. Set operations

  46. Complements

  47. Logical operations

  48. Single-pixel operations

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