We are now able to generalize our analysis for arbitrary filters
H0
H0
,
H1
H1
,
G0
G0
and
G1
G1
. Substituting this equation and this equation in our
discussion of 2-band filter bank into this earlier equation and then
using this equation and this equation from the same discussion, we
get:
X
^
z=12G0zY0z+Y0-z+12G1zY1z+Y1-z=12G0zH0zXz+12G0zH0-zX-z+12G1zH1zXz+12G1zH1-zX-z=12XzG0zH0z+G1zH1z+12X-zG0zH0-z+G1zH1-z
X
^
z
1
2
G0
z
Y0
z
Y0
z
1
2
G1
z
Y1
z
Y1
z
1
2
G0
z
H0
z
X
z
1
2
G0
z
H0
z
X
z
1
2
G1
z
H1
z
X
z
1
2
G1
z
H1
z
X
z
1
2
X
z
G0
z
H0
z
G1
z
H1
z
1
2
X
z
G0
z
H0
z
G1
z
H1
z
(1)
If we require
X
^
z≡Xz
X
^
z
X
z
- the Perfect Reconstruction (PR) condition - then:
G0zH0z+G1zH1z≡2
G0
z
H0
z
G1
z
H1
z
2
(2)
and
G0zH0-z+G1zH1-z≡0
G0
z
H0
z
G1
z
H1
z
0
(3)
Identity
Equation 3 is known as the
anti-aliasing condition because the term in
X-z
X
z
in
Equation 1 is the unwanted
aliasing term caused by down-sampling
y0
y0
and
y1
y1
by 2.
It is straightforward to show that the expression for
H0
H0
,
H1
H1
,
G0
G0
and
G1
G1
, given in this equation, this equation, this equation
and this equation for the filters based on the Haar transform,
satisfy Equation 2 and Equation 3. They are the simplest set of
filters which do.
Before we look at more complicated PR filters, we examine how
the filter structures of this figure may be extended to form a
binary filter tree (and the discrete wavelet transform).