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lecture13_ImageRestoration

lecture13_ImageRestoration - Image Restoration Yao Wang...

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Image Restoration Yao Wang Polytechnic Institute of NYU, Brooklyn, NY 11201 Partly based on A. K. Jain, Fundamentals of Digital Image Processing, and Gonzalez/Woods, Digital Image Processing Figures from Gonzalez/Woods, Digital Image Processing
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Yao Wang, NYU-Poly EL5123: Image Restoration 2 Lecture Outline Introduction Image degradation model Blurring caused by finite camera exposure Blurring caused by motion Inverse filtering Wiener filter
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Yao Wang, NYU-Poly EL5123: Image Restoration 3 Examples
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Yao Wang, NYU-Poly EL5123: Image Restoration 4 Degradation Model General model g(x,y)= T (f(x,y)) + n(x,y) T( ) may not be linear Modeling T ( ) by a filtering operation g(x,y)= f(x,y) * h(x,y) + n(x,y) This means that the degradation operator is linear and shift invariant h(x,y) is unknown and needs to be estimated (system identification problem) Given h(x,y) and some statistics of n(x,y), how to recover f(x,y) from g(x,y)? How to estimate h(x,y) and statistics of n(x,y)?
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Yao Wang, NYU-Poly EL5123: Image Restoration 5 Degradation due to Finite Size Sensor Ideally the value of a pixel should be the light
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