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Digital Image Processing

Les 10 meilleurs produits en mai 2025
Dernière mise à jour : 28 mai 2025
Techleens IT Solutions
Techleens IT Solutions
Digital Image Processing Quiz (BSCS)            
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Amazon.fr
#3

  • 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
Ashish Kumar
Digital Image Processing                        
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Amazon.fr
#8

  • 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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