Coiflet

Coiflet with two vanishing moments

Coiflets are discrete wavelets designed by Ingrid Daubechies, at the request of Ronald Coifman, to have scaling functions with vanishing moments. The wavelet is near symmetric, their wavelet functions have N / 3 vanishing moments and scaling functions N / 3 − 1, and has been used in many applications using Calderón-Zygmund Operators.^[1][2]

Coiflet coefficients

Both the scaling function (low-pass filter) and the wavelet function (High-Pass Filter) must be normalised by a factor $1/\sqrt{2}$. Below are the coefficients for the scaling functions for C6-30. The wavelet coefficients are derived by reversing the order of the scaling function coefficients and then reversing the sign of every second one (ie. C6 wavelet = {−0.022140543057, 0.102859456942, 0.544281086116, −1.205718913884, 0.477859456942, 0.102859456942}).

Mathematically, this looks like B_k = ( − 1)^kC_{N − 1 − k} where k is the coefficient index, B is a wavelet coefficient and C a scaling function coefficient. N is the wavelet index, ie 6 for C6.

Coiflets coefficients

k	C6	C12	C18	C24	C30
-10					-0.0002999290456692
-9					0.0005071055047161
-8				0.0012619224228619	0.0030805734519904
-7				-0.0023044502875399	-0.0058821563280714
-6			-0.0053648373418441	-0.0103890503269406	-0.0143282246988201
-5			0.0110062534156628	0.0227249229665297	0.0331043666129858
-4		0.0231751934774337	0.0331671209583407	0.0377344771391261	0.0398380343959686
-3		-0.0586402759669371	-0.0930155289574539	-0.1149284838038540	-0.1299967565094460
-2	-0.1028594569415370	-0.0952791806220162	-0.0864415271204239	-0.0793053059248983	-0.0736051069489375
-1	0.4778594569415370	0.5460420930695330	0.5730066705472950	0.5873348100322010	0.5961918029174380
0	1.2057189138830700	1.1493647877137300	1.1225705137406600	1.1062529100791000	1.0950165427080700
1	0.5442810861169260	0.5897343873912380	0.6059671435456480	0.6143146193357710	0.6194005181568410
2	-0.1028594569415370	-0.1081712141834230	-0.1015402815097780	-0.0942254750477914	-0.0877346296564723
3	-0.0221405430584631	-0.0840529609215432	-0.1163925015231710	-0.1360762293560410	-0.1492888402656790
4		0.0334888203265590	0.0488681886423339	0.0556272739169390	0.0583893855505615
5		0.0079357672259240	0.0224584819240757	0.0354716628454062	0.0462091445541337
6		-0.0025784067122813	-0.0127392020220977	-0.0215126323101745	-0.0279425853727641
7		-0.0010190107982153	-0.0036409178311325	-0.0080020216899011	-0.0129534995030117
8			0.0015804102019152	0.0053053298270610	0.0095622335982613
9			0.0006593303475864	0.0017911878553906	0.0034387669687710
10			-0.0001003855491065	-0.0008330003901883	-0.0023498958688271
11			-0.0000489314685106	-0.0003676592334273	-0.0009016444801393
12				0.0000881604532320	0.0004268915950172
13				0.0000441656938246	0.0001984938227975
14				-0.0000046098383254	-0.0000582936877724
15				-0.0000025243583600	-0.0000300806359640
16					0.0000052336193200
17					0.0000029150058427
18					-0.0000002296399300
19					-0.0000001358212135

References

1. ^ G. Beylkin, R. Coifman, and V. Rokhlin (1991),Fast wavelet transforms and numerical algorithms, Comm. Pure Appl. Math., 44, pp. 141-183
2. ^ Ingrid Daubechies, Ten Lectures on Wavelets, Society for Industrial and Applied Mathematics, 1992, ISBN 0-89871-274-2