sparse image representation via combined transforms - Convex ...
sparse image representation via combined transforms - Convex ...
sparse image representation via combined transforms - Convex ...
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78 CHAPTER 3. IMAGE TRANSFORMS AND IMAGE FEATURES<br />
Equations (3.38) (3.39) and (3.40) together are equivalent to the matrix multiplication<br />
(<br />
H(z) H(−z)<br />
)(<br />
H(z −1 ) H(−z −1 )<br />
)<br />
(<br />
2 0<br />
)<br />
G(z)<br />
G(−z)<br />
G(z −1 ) G(−z −1 )<br />
=<br />
0 2<br />
.<br />
Taking the determinant of both sides, we have<br />
[H(z)G(−z) − G(z)H(−z)][H(z −1 )G(−z −1 ) − G(z −1 )H(−z −1 )] = 4. (3.41)<br />
If both sequence {h(n) :n ∈ Z} and sequence {g(n) :n ∈ Z} have finite length (thinking of<br />
the impulse responses of FIR filters), then the polynomial H(z)G(−z) − G(z)H(−z) must<br />
have only one nonzero term. Since if the polynomial H(z)G(−z) − G(z)H(−z) has more<br />
than two terms and simultaneously has finite length, (3.41) can never be equal to a constant.<br />
On the other hand, we have<br />
[H(z −1 )+H(−z −1 )][H(z)G(−z) − G(z)H(−z)]<br />
= H(z −1 )H(z)G(−z)+H(−z −1 )H(z)G(−z)<br />
−H(z −1 )G(z)H(−z) − H(−z −1 )G(z)H(−z)<br />
(3.40)<br />
= H(z −1 )H(z)G(−z) − H(z −1 )H(z)G(z)<br />
+H(−z −1 )G(−z)H(−z) − H(−z −1 )G(z)H(−z)<br />
(3.38)<br />
= 2[G(−z) − G(z)].<br />
We know that H(z)G(−z) − G(z)H(−z) only has one nonzero term. The polynomial<br />
H(z −1 )+H(−z −1 ) can only have terms with even exponents and polynomial G(−z) − G(z)<br />
can only have terms with odd exponents, so from the previous equation, there must exist<br />
an integer k, such that<br />
H(z)G(−z) − G(z)H(−z) =2z 2k+1 ,<br />
and<br />
[H(z −1 )+H(−z −1 )]z 2k+1 = G(−z) − G(z). (3.42)