Chapter 1. Introduction

1. Chapter 1. Introduction

2. Goals of Image Processing • “One picture is worth more than a thousand words” • Improvement of pictorial information for human interpretation. • Processing of scene data for autonomous machine perception.

3. Related Areas of Image Processing • Image Processing: image  image • Computer Graphics: information  image • Computer Vision: image  information

4. Applications of Image Processing • Image Analysis • Image Restoration • Image Enhancement • Image Compression

5. Example of Image Restoration

6. Example of Image Enhancement

7. Steps in Digital Image Processing

8. Digital Image

9. Sampling & Quantization

10. Sampling

11. Quantization False contours

12. Storage requirement A MxN image with 2k gray scales # of storage bits = M x N x k

13. Example Generally, transmission is accomplished in packets consisting of a start bit, a byte of information, and a stop bit. Using this approach, how many seconds would it take to transmit a 1024x1024 image with 256 gray levels at 300 baud (bits/sec)?

14. Types of Images • Analog Image • Digital Image • Binary Image • Gray-scale Image • Color Image • Multispectral Image

15. Multispectral Image

16. Electromagnetic Spectrum

17. Image Formats • Vector Image • Bitmap Image • RAW  no header • RLE (Run-Length Encoding) • PGM,PPM,PNM (Portable Gray Map) • GIF (Graphics Interchange Format)  no more than 256 colors • TIF (Tag Image File Format)  Scanner • EPS (Encapsulated Postscript)  Printer • JPEG (Joint Photographic Experts Group)  Compression ratio • MPEG (Motion Picture Experts Group)  Video

18. Comparison of Image Formats

19. Human Visual Perception

20. Machine Visual Perception

21. Perception of objects • The spectrum (energy) of light source. • The spectral reflectance of the object surface. • The spectral sensitivity of the sensor (eye or camera).

22. Human eye

23. How do we see an object? Light Eye Object • Luminance  Lightness  Rods • Chrominance  Color  Cones Human eye is more sensitive to luminance than to chrominance

24. Cones & Rods( day & night )

25. Three kinds of Cones

26. Brightness adaptation

27. Brightness illusions: Mach band effect

28. Contrast illusions

29. Geometric illusions

30. Spatial & Temporal Resolution • Spatial resolution: 4-50 cycles per degree • Temporal resolution: 50 cycles per second • Brightness resolution: 100 gray levels

31. Color Spectrum

32. Electromagnetic spectrum

33. RGB Model

34. RGB Model

35. RGB signals from a video camera

36. RGB Model • Color measurement: • A mixture of red, green, and blue light • Values between 0.0 (none) and 1.0 (lots) • Color examples • Red Green Blue • White 1.0 1.0 1.0 • Black 0.0 0.0 0.0 • Yellow 1.0 1.0 0.0 • Magenta 1.0 0.0 1.0 • Cyan 1.0 1.0 0.0

37. rgb Model(Normalized RGB) r+g+b=1

38. Chromaticity Diagram

39. Typical color gamut

40. HSI Model

41. HSI Model

42. Color Complements

43. CMY Model

44. Light vs. Pigment

45. YIQ Model • TV transmission  digital space  YCBCR •  analog space  YIQ (NTSC) •  YUV (PAL)

46. YUV & YCBCR Model

47. TV Broadcast