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Lecture 12

Lecture 12. Figures from Gonzalez and Woods, Digital Image Processing, Second Edition, 2002. Image Restoration. Chapter 5 Image Restoration. Spatial and Frequency Properties of Noise. Assumptions about noise Noise is independent of spatial coordinates (except spatially periodic noise)

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Lecture 12

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  1. Lecture 12 Figures from Gonzalez and Woods, Digital Image Processing, Second Edition, 2002.

  2. Image Restoration

  3. Chapter 5 Image Restoration

  4. Spatial and Frequency Properties of Noise Assumptions about noise • Noise is independent of spatial coordinates (except spatially periodic noise) • Uncorrelated with respect to image itself (actual pixel values) These assumptions are not strictly true( X-ray and nuclear medicine imaging, for instance. Under such assumptions, we have noise density functions

  5. Chapter 5 Image Restoration

  6. Types of noise typical for these distributions • Gaussian noise– Electronic circuits and sensor noise • Rayleigh noise– noise fom range imaging • Exponential and Gamma Densities – Laser imaging • Impulse noise – From situations where quick transients, such as faulty switching, take place during imaging • Uniform noise– Used for random number generators, not really descriptive of applications

  7. Chapter 5 Image Restoration

  8. Chapter 5 Image Restoration

  9. Chapter 5 Image Restoration

  10. Chapter 5 Image Restoration

  11. Estimating Noise Parameters

  12. Chapter 5 Image Restoration

  13. Spatial Domain Noise Filters(1)

  14. Chapter 5 Image Restoration

  15. Spatial Domain Noise Filters(2)

  16. Chapter 5 Image Restoration

  17. Chapter 5 Image Restoration

  18. Spatial Domain Noise Filters(3)

  19. Spatial Domain Filters (4)

  20. Chapter 5 Image Restoration

  21. Chapter 5 Image Restoration

  22. Spatial Domain Noise Filters (5)

  23. Chapter 5 Image Restoration

  24. Chapter 5 Image Restoration

  25. Adaptive Spatial Filters • Local noise reduction filter • Adaptive Mean filter

  26. Chapter 5 Image Restoration

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