113_1_EE113_illustrations_convolution

113_1_EE113_illustra - Illustration of EE113 concepts in practice Convolution Convolution Image enhancement using filtering in the spatial domain 1

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1 Illustration of EE113 concepts in practice Illustration of EE113 concepts in practice ± Convolution Convolution Image enhancement using filtering in the spatial Image enhancement using filtering in the spatial domain domain
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2 Image Enhancement Using Filtering In the Spatial Domain ± 2-D signal passes through a system T : ± A system is linear : ± A system is shift (time) invariant : ± The LTI system can be completely characterized by its impulse response : ) , ( 2 1 n n x [ ] ) , ( ) , ( 2 1 2 1 n n x T n n y = [] ) , ( ) , ( ) , ( ) , ( 2 1 2 2 2 1 1 1 2 1 2 2 2 1 1 1 n n y a n n y a n n x a n n x a T + = + ) , ( ) , ( 2 2 1 1 2 2 1 1 m n m n y m n m n x T = [ ] ) , ( ) , ( 2 1 2 1 n n T n n h δ = ) , ( ) , ( ) , ( 2 2 1 1 2 1 2 1 12 k n k n h kk k k x n n y = ∑∑ −∞ = −∞ = 2-D convolution
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3 A Typical 2-D Convolution h(n1,n2) y(n1,n2)=x*h (N+M-2) (M-1) (M-1) x(n1,n2) (N-1) (N-1) (N+M-2) ) , ( ) , ( ) , ( 2 2 1 1 2 1 2 1 12 k n k n h kk k k x n n y = ∑∑ −∞ = −∞ =
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4 2 3 3 1 6 10 10 4 6 10 10 4 4 7 7 3
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This note was uploaded on 02/09/2011 for the course EE 113 taught by Professor Walker during the Spring '08 term at UCLA.

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113_1_EE113_illustra - Illustration of EE113 concepts in practice Convolution Convolution Image enhancement using filtering in the spatial domain 1

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