12_noisex

12_noisex - Noise Models COMP344 COMP344 Noise Models...

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Unformatted text preview: Noise Models COMP344 COMP344 Noise Models Probability Density Functions The statistical behavior of the gray-level values in the noise component can be described by some probability density functions p ( x ) ≥ 0 for all x R ∞-∞ p ( x ) dx = 1 (the total area under the graph is 1) for any two numbers a and b , the probability of the interval [ a , b ] is given by Z b a p ( x ) dx COMP344 Noise Models Probability Density Functions... Mean (aka expected value or expectation ) E ( X ) = Z ∞-∞ xp ( x ) dx r th Moment : E ( X r ) mean μ = E ( X ): 1st moment r th Central Moment : μ r = E [( X- μ ) r ] μ = 1 ,μ 1 = 0 ,μ 2 = variance COMP344 Noise Models Gaussian Noise p ( z ) = 1 √ 2 πσ e- ( z- μ ) 2 2 σ 2 z : random variable μ : mean ; σ : standard derivation e.g., electronic circuit noise and sensor noise due to poor illumination and/or high temperature COMP344 Noise Models Rayleigh Noise p ( z ) = 2 b ( z- a ) e- ( z- a ) 2 / b z ≥ a z < a mean: μ = a + q π b 4 ; variance:...
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12_noisex - Noise Models COMP344 COMP344 Noise Models...

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