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e178-L7 - Averaging g x y = f x y x y 1M g x y = gi x y M i...

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Local Enhancement 1 Averaging Fig 3.30 and Uncorrelated zero mean duces the noise variance 2 2 2 g x y f x y x y g x y M g x y E g x y f x y M x y x y x y i i M g ( , ) ( , ) ( , ) ( , ) ( , ) ( ( , )) ( , ) ( , ) ( , ) ( , ) Re = + = = = = η σ σ η σ η η 1 1 1 Spatial Filtering Chapter 3 Required Reading: All sections except 3.8 Local Enhancement 2
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Image Forensics Project Guidelines Process Images Local Enhancement 3 Local Enhancement 4 Fig 3.30
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Local Enhancement 5 Another example Images with additive Gausian Noise; Independent Samples. I=imnoise(J,’Gaussian’); Local Enhancement 6 Averaged image Left: averaged image (10 samples); Right: original image
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Local Enhancement 7 Spatial filtering Frequency Spatial 0 LPF HPF BPF Local Enhancement 8 Smoothing (Low Pass) Filtering ω 1 ω 2 ω 3 ω 4 ω 5 ω 6 ω 7 ω 8 ω 9 f 1 f 2 f 3 (x,y) Replace f (x,y) with Linear filter LPF: reduces additive noise blurs the image sharpness details are lost (Example: Local averaging) Fig 3.35 f x y f i i i ^ ( , ) = ω
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Local Enhancement 9 Fig 3.35: smoothing Local Enhancement 10 Fig 3.36: another example
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