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A library of image forensics algorithms for tampering localization.
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package DWT;
/**
* Author Mark Bishop; 2014
* License GNU v3;
* This class is free software: you can redistribute it and/or modify
it under the terms of the GNU General Public License as published by
the Free Software Foundation, either version 3 of the License, or
(at your option) any later version.
This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
GNU General Public License for more details.
You should have received a copy of the GNU General Public License
along with this program. If not, see validParameters(Wavelet wavelet) {
ArrayList result = new ArrayList();
switch (wavelet) {
case Haar:
result.add(2);
break;
case Daubechies:
for (int i = 4; i <= 20; i += 2) {
result.add(i);
}
break;
case Beylkin:
result.add(18);
break;
case Vaidyanathan:
result.add(24);
break;
case Coiflet:
for (int i = 6; i <= 30; i += 6) {
result.add(i);
}
break;
case Symmlet:
for (int i = 4; i <= 10; i++) {
result.add(i);
}
break;
case Battle:
result.add(1);
result.add(3);
break;
}
return result;
}
/**
*
* @param parameter To be explained
* @param wavelet To be explained
* @param signalLength To be explained
* @return A list of valid scales for a given wavelet and signal length.
* @throws Exception
*/
public static ArrayList validScales(int parameter,
Wavelet wavelet, int signalLength) throws Exception {
ArrayList validScales = new ArrayList();
int hLength = OrthogonalFilters.getLowPass(wavelet, parameter).length;
if (hLength > signalLength) {
throw new Exception("The filter is longer than the signal.");
}
int log2SigLen = (int) (Math.log(signalLength) / Math.log(2));
int min = (int) (Math.log(hLength) / Math.log(2));
for (int i = min; i <= log2SigLen; i++) {
double t = Math.log(hLength);
if (t < min) {
validScales.add(i);
}
}
return validScales;
}
}
// Some descriptive narrative from the Wavelab project:
//
// Description
// The Haar filter (which could be considered a Daubechies-2) was the
// first wavelet, though not called as such, and is discontinuous.
//
// The Beylkin filter places roots for the frequency response function
// close to the Nyquist frequency on the real axis.
//
// The Coiflet filters are designed to give both the mother and father
// wavelets 2*Par vanishing moments; here Par may be one of 1,2,3,4 or 5.
//
// The Daubechies filters are minimal phase filters that generate wavelets
// which have a minimal support for a given number of vanishing moments.
// They are indexed by their length, Par, which may be one of
// 4,6,8,10,12,14,16,18 or 20. The number of vanishing moments is par/2.
//
// Symmlets are also wavelets within a minimum size support for a given
// number of vanishing moments, but they are as symmetrical as possible,
// as opposed to the Daubechies filters which are highly asymmetrical.
// They are indexed by Par, which specifies the number of vanishing
// moments and is equal to half the size of the support. It ranges
// from 4 to 10.
//
// The Vaidyanathan filter gives an exact reconstruction, but does not
// satisfy any moment condition. The filter has been optimized for
// speech coding.
//
// The Battle-Lemarie filter generate spline orthogonal wavelet basis.
// The order Par gives the degree of the spline. The number of
// vanishing moments is Par+1.
//
//