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

22.  Saturation and noise

23.  Number of storage bits

24.  Spatial and gray-level resolution

25.  Subsampled and resampled

26.  Reducing spatial resolution

27.  Varying the number of gray levels

29.  N and k in different-details images

30.  Isopreference

31.  Interpolations

32.  Zooming and shrinking

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

34.  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

35. 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

37.  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

38.  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

39.  Distance measures Euclidean distance City-block distance Chessboard distance

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

41. 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,

42.  Arithmetic operations Addition

43.  Arithmetic operations Subtraction

44. Digital subtraction angiography

45. Shading correction

46.  Image multiplication

47.  Set operations

48.  Complements

49.  Logical operations

50.  Single- pixel operations

51.  Neighborhood operations

52.  Affine transformations

53.  Inverse mapping

54.  Registration

55.  Vector operations

56.  Image transforms

57.  Fourier transform

58.  Probabilistic methods