/**
* Constructor with default Gaussian kernel [1/16, 1/4, 3/8, 1/4, 1/16] for at most dimension x, y
* (and z if present).
*
* @param img input image
* @param Jmax maximum scale (2^Jmax - 1)
* @param denoise reduction of gaussian noise
* @throws ALDOperatorException
*/
public UndecimatedWaveletTransform(MTBImage _img, int _Jmax, boolean _denoise)
throws ALDOperatorException {
this.m_statusListeners = new Vector<StatusListener>(1);
this.setImg(_img);
this.setJmax(_Jmax);
this.setForwardTransform();
this.setDenoise(_denoise);
double[] kernel = {1.0 / 16.0, 1.0 / 4.0, 3.0 / 8.0, 1.0 / 4.0, 1.0 / 16.0};
MTBImage[] kernels;
if (_img.getSizeZ() > 1) {
kernels = new MTBImage[3];
kernels[0] = MTBImage.createMTBImage(5, 1, 1, 1, 1, MTBImageType.MTB_DOUBLE);
kernels[1] = MTBImage.createMTBImage(1, 5, 1, 1, 1, MTBImageType.MTB_DOUBLE);
kernels[2] = MTBImage.createMTBImage(1, 1, 5, 1, 1, MTBImageType.MTB_DOUBLE);
for (int i = 0; i < kernel.length; i++) {
kernels[0].putValueDouble(i, 0, 0, 0, 0, kernel[i]);
kernels[1].putValueDouble(0, i, 0, 0, 0, kernel[i]);
kernels[2].putValueDouble(0, 0, i, 0, 0, kernel[i]);
}
} else {
kernels = new MTBImage[2];
kernels[0] = MTBImage.createMTBImage(5, 1, 1, 1, 1, MTBImageType.MTB_DOUBLE);
kernels[1] = MTBImage.createMTBImage(1, 5, 1, 1, 1, MTBImageType.MTB_DOUBLE);
for (int i = 0; i < kernel.length; i++) {
kernels[0].putValueDouble(i, 0, 0, 0, 0, kernel[i]);
kernels[1].putValueDouble(0, i, 0, 0, 0, kernel[i]);
}
}
this.setKernels(kernels);
this.operatorExecStatus = OperatorExecutionStatus.OP_EXEC_INIT;
}
