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Signals Through Linear Shift-Invariant Systems
Definitions
A system (operator) H is called linear if for every two signals and constants a,b:
A system (operator) H is called shift-invariant (or time-invariant) if for each signal :
Operators can be both linear and SI, or neither. It is also possible for an operator to be SI but not linear, or linear but not SI.
1 2( ), ( )t t
1 2 1 2( ) ( ) ( ) ( )H a t b t a H t b H t
( )t
0 0( ) ( )t tH T t T H t
The Impulse Response of an LSI System
The impulse response of an LSI system H, is the result of H operating on a delta function . It is often marked ( )LSIH t ( )LSIh t
( )LSIh t( )t H
Proporties of LSI Systems
Every LSI operation can be expressed as a convolution between the input signal and the system's impulse response . Mathematically: for each LSI system H and for each input signal :
Proof: Let H be an LSI system and let be its input signal.
( )t ( )LSIh t( )t
( ) ( ) ( )LSIH t t h t ( )t
(1) (2) (3)
(4) (5)
( ) ( ) ( ) ( ) ( ) ( ) ( ) ( )
( ) ( ) ( ) ( )LSI LSI
H t H t d H t d H t t d
h t d t h t
( ) ( )LSIh t t( )t H
Proporties of LSI Systems
Let H1,H2 be two LSI systems, then:
Proof:
1 2 2 1( ) ( )H H t H H t
1 2 1 2 1 2 1 2(1) (2) (3)
2 1 2 1 2 1 2 1(4) (5) (6) (7)
( ) ( ) ( ) ( )
( ) ( ) ( ) ( )
H H t H H t H h t h h t
h h t H h t H H t H H t
LSI Operators On Orthonormal Families
Let be an orthonormal family.
Let . We want to check if are orthonormal.
If by some miracle this family satisfies such that
then the inner product would be:
we say that the functions are eigenfuctions of H and are their eigenvalues.
0( ), ( ) ( )
N
k l i it t t
( ) , ( )k lH t H t
1 i n ( )H i
( ) ( ) ( )i H iH t i t
(1)
(2)
( ) , ( ) ( ) ( ) ( ) ( ) ( ) ( )
1( ) ( ) ( ) ( ) ( ) ( )
0
k l k l H k H l
H H k l H H
H t H t H t H t dt k t l t dt
k lk l t t dt k l
k l
0( )
N
i it
( )H i
0( )
N
i it
The Majestic Family
Let H be an LSI system, then for each
, where
Proof:
( ) ( ) ( )k H kH t k t ( ) ( ) ( )H k F h t k
2 2 ( )
(1) (2)
2 2
(3)
( ) ( ) ( ) ( ) ( )
( ) ( ) ( )
i k i k tk k
i k t i kk
H t h t d e h t d e h d
e e h d t F h t
The Majestic Family
As a result, when the signal (the representation of the signal in the Fourier basis) goes through an LSI system, the result is also a linear combination of with new coefficients :
Another important conclusion is the following theorem:
Proof:
0
ˆ( ) ( )N
i ii
t t
( )t
0( )
N
i it
( )i i H i
(1) (2)
0 0 0
( ) ( ) ( ) ( )N N N
i i i i i H ii i i
H t H t i t
( ) ( ) ( ) ( )k kF t h t F t F h t
(1) (2) (3)( ) ( ) ( ) ( ) ( ) ( ) ( ) ( )k H k H k kF t h t F k t k F t F t F h t
Example of Medical Usage of LSI Ops.
Laplacian filter of bone scan (a)
Sharpened version of bone scan achieved by subtracting (a) and (b) Sobel filter of bone
scan (a)
(a)
(b)
(c)
(d)
Meet Bob!
Example of Medical Usage
Sharpened image which is sum of (a) and (f)
Result of applying a power-law trans. to (g)
(e)
(f)
(g)
(h)
The product of (c) and (e) which will be used as a mask
Image (d) smoothed with a 5*5 averaging filter
BEFORE: AFTER: