Digital Image Processing
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15 novembre 2024
PEARSON INDIA
Digital Image Processing, 4Th Edition
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Pearson
Digital Image Processing, Global Edition
Spedizione gratuita
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Prentice Hall
Digital Image Processing
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#3
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Books In Good Condition
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Springer
Digital Image Processing: An Algorithmic Introduction Using Java
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Springer
Digital Image Processing: An Algorithmic Introduction Using Java
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Techleens IT Solutions
Digital Image Processing Quiz (BSCS)
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Digital image processing app is organized into chapters including 600+ DIP MCQs with answer key
Digital image processing quick study guide questions and answers covers topics: Color image processing, digital image fundamentals, filtering in frequency domain, image compression, image restoration and reconstruction, image segmentation, intensity transformation and spatial filtering, introduction to digital image processing, morphological image processing, wavelet and multiresolution processing
This digital image processing distance learning resource provides interactive quizzes for quick test preparation
Each chapter includes a collection of MCQs to practice digital image processing exam questions
Practice digital image processing quick study guide to improve computer science skills with self-assessment
Job seekers can prepare for interviews and career tests with this competitive exams app
This Online Learning App helps in teaching to ask questions to students during online classes and tutorials
Digital Image Processing Quick Review App provides quick preparation for CS certifications and exams
Digital Image Processing Learning app helps for exam prep for teaching jobs, research jobs, and computer science related jobs
This e-learning study guide is very beneficial for distance education and online education
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Ashish Kumar
Digital Image Processing
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This unique free application is for all students across the world. It covers 128 topics of Digital image processing in detail. These 128 topics are divided in 7 units.
Each topic is around 600 words and is complete with diagrams, equations and other forms of graphical representations along with simple text explaining the concept in detail.
This USP of this application is "ultra-portability". Students can access the content on-the-go from anywhere they like.
Basically, each topic is like a detailed flash card and will make the lives of students simpler and easier.
Some of topics Covered in this 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
20. Smoothing filters
21. Sharpening filters
22. Derivative filters
23. Laplacian filters
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
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
94. Eroding an Image
95. Combination of Dilation and Erosion
96. Dilation- and Erosion-Based Functions
97. Hole filling
98. Convex hull
99. Thinning
100. Thickening
101. Skeletonization
102. Pruning
103. Closing operator
104. Opening operator
105. Hit-and-Miss Transform
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Digital Image Processing 3rd Edition
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#8
Prentice Hall
Digital Image Processing Using Matlab
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#9
CRC Press
Forensic Digital Image Processing: Optimization of Impression Evidence
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#10
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