Filtering in Computer Vision - Lecture 2

Filtering in Computer Vision - Lecture 2

UCF CRCV via YouTube Direct link

Derivatives and Noise

31 of 34

31 of 34

Derivatives and Noise

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Classroom Contents

Filtering in Computer Vision - Lecture 2

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  1. 1 General
  2. 2 Binary Images
  3. 3 Gray Level Image
  4. 4 Gray Scale Image
  5. 5 Color Image Red, Green, Blue Channels
  6. 6 Image Histogram
  7. 7 Image Noise
  8. 8 Gaussian Noise
  9. 9 Definitions
  10. 10 Discrete Derivative Finite Difference
  11. 11 Derivatives in 2 Dimensions
  12. 12 Derivatives of Images
  13. 13 Correlation
  14. 14 Convolution
  15. 15 Averages
  16. 16 Gaussian Filter
  17. 17 Properties of Gaussian
  18. 18 Linear Filtering
  19. 19 Filtering Examples
  20. 20 Blurring Examples
  21. 21 Filtering Gaussian
  22. 22 Gaussian vs. Smoothing
  23. 23 Noise Filtering
  24. 24 MATLAB Functions
  25. 25 An Application
  26. 26 Edge Detection in Images
  27. 27 What is an Edge?
  28. 28 Detecting Discontinuities
  29. 29 Derivative in Two-Dimensions
  30. 30 Image Derivatives
  31. 31 Derivatives and Noise
  32. 32 Image Smoothing
  33. 33 Gaussian Smoothing (Examples)
  34. 34 Edge Detectors

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