Digital Image Processing

Handbook of Digital Image Processing with diagrams, learn a topic in a minute

The app is a complete free handbook of Digital Image Processing which covers important all topics with detailed notes, diagrams, equations, formulas & course material.

The App is designed for quick learning, revisions, references at the time of exams and interviews.

This Engineering eBook cover most of related topics and Detailed explanation with all the basics topics.

Some of topics Covered in this Digital Image Processing application are:

1. Global properties using B-rep model

2. Compression fundamentals

3. Lossless data compression

4. Image restoration

5. Linear position invariant degradation models

6. Elements of visual perception

7. Color perception

8. Image sampling and quantization

9. Basic relationship between pixels

10. Basic geometric transformations

11. Introduction to Fourier transform and DFT

12. Fast Fourier transform

13. Properties of two dimensional Fourier transform

14. Separable image transforms

15. Walsh, Hadamard, discrete cosine, Haar and Slant transforms

16. Spatial domain methods

17. Grey scale manipulation and histogram equalization

18. Image subtraction and Image averaging

19. Spatial filtering on images

20. Smoothing filters on images

21. Sharpening filters on images

22. Derivative filters on images

23. Laplacian filters on images

24. Frequency domain

25. Homomorphic filtering

26. Image restoration process

27. Model of image degradation

28. Noise models

29. Characteristics of the noise models

30. Order-Statistics Filters

31. Adaptive filters - Digital Image Processing

32. Least-Mean-Square (LMS) Algorithm

33. Blind Image Restoration and Recognition

34. Pseudo-Inverse Filtering

35. Singular value decomposition

36. Lossless compression

37. Lossy compression

38. Lempel-Ziv-Welch (LZW) Compression

39. Lempel-Ziv-Welch (LZW) decompression

40. Bit plane coding

41. Differential Pulse Code Modulation (DPCM)

42. Image representation

43. Transform Coding

44. Wavelet Image Coding

45. JPEG Compression

46. MPEG Compression

47. Basics of Vector quantization

48. Image Segmentation

49. Edge Detection

50. Image thresholding

51. Region based segmentation

52. Boundary Representation Models

53. Data structure of boundary representation models

54. Vertex-based boundary model

55. Face-based boundary models

56. Graph representation

57. Validity of boundary models

58. Faceted modelers for some B-rep systems

59. Two-and-half dimensional drawing

60. Advantage and disadvantage of boundary representation

61. Polygonal approximation

62. Algorithm for closed contours

63. Solution for closed contours

64. Heuristic algorithms

65. Multiple-object polygonal approximation

66. Optimal algorithms for min-# problem

67. Iterative reduced search

68. Boundary Descriptors

69. Radial Distance Measures

70. Linear Discriminant Analysis

71. Reduced search algorithm

72. The Hough transform

73. Edge detection techniques

74. Laplacian of Gaussian

75. Canny - Edge Detection Algorithm

76. Fundamentals of color

77. The RGB Color Model

78. Additive vs. Subtractive Color Models

79. Interactive Specification of Color

80. Colour Image Processing

81. CIE primaries

82. The HSI Model

83. The YIQ Model

84. Transferring Color to Greyscale Images

85. Basics of Full-Colour Image Processing

86. Colour Slicing

87. Tone and Colour Corrections

88. Intensity slicing

89. Intensity to color transformation

90. Morphological Image Processing

91. Dilating an Image

92. Structuring Elements

93. Structuring Element Decomposition

All topics are not listed because of character limitations.

Each topic is complete with diagrams, equations and other forms of graphical representations for better learning and quick understanding.

This app will useful for quick reference. The revision of all concepts can be finished within Several hour using this app.

Digital Image Processing is part of engineering education courses and technology degree programs of various universities.