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

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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

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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

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11. Estimating Noise Parameters

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13. Spatial Domain Noise Filters(1)

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15. Spatial Domain Noise Filters(2)

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18. Spatial Domain Noise Filters(3)

19. Spatial Domain Filters (4)

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22. Spatial Domain Noise Filters (5)

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

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