Difference between revisions of "Short Notes on Wavelets"
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Note that resulting values typically use 1 more bit than original ones - if source values are in [0..N) interval, then resulting values are in (-N, N) interval. | Note that resulting values typically use 1 more bit than original ones - if source values are in [0..N) interval, then resulting values are in (-N, N) interval. | ||
| − | + | === Using Lists === | |
<pre>def haar_int_fwd_1d(d): | <pre>def haar_int_fwd_1d(d): | ||
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hp = [i + j for i, j in zip(lp, odd)] | hp = [i + j for i, j in zip(lp, odd)] | ||
return [x for t in zip(lp, hp) for x in t]</pre> | return [x for t in zip(lp, hp) for x in t]</pre> | ||
| + | |||
| + | === Using numpy array's === | ||
| + | |||
| + | TBP | ||
Revision as of 15:14, 24 February 2017
Integer Haar Wavelets, Python implementation
This is a trivial implementation of Haar integer-to-integer wavelets. Note that resulting values typically use 1 more bit than original ones - if source values are in [0..N) interval, then resulting values are in (-N, N) interval.
Using Lists
def haar_int_fwd_1d(d):
if len(d) == 1:
return d
even = d[::2]
odd = d[1::2]
hp = [j - i for i, j in zip(even, odd)]
lp = [i + (w >> 1) + (w % 2) for i, w in zip(even, hp)]
return haar_int_fwd_1d(lp) + hp
def haar_int_inv_1d(d):
if len(d) == 1:
return d
even = haar_int_inv_1d(d[:len(d) >> 1])
odd = d[len(d) >> 1:]
lp = [i - (j >> 1) - (j % 2) for i, j in zip(even, odd)]
hp = [i + j for i, j in zip(lp, odd)]
return [x for t in zip(lp, hp) for x in t]
Using numpy array's
TBP
