# 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 16:14, 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