/// <summary>
/// Forward Laplacian pyramid transform.
/// </summary>
/// <param name="data">Gaussian pyramid</param>
/// <returns>Pyramid</returns>
public float[][,] Forward(float[][,] data)
{
int nlev = data.Length;
float[][,] lapl = new float[nlev][, ];
for (int i = 1; i < nlev; i++)
{
lapl[i - 1] = GaussianPyramidTransform.sub(data[i - 1], GaussianPyramidTransform.upsample(data[i], this.radius));
}
lapl[nlev - 1] = data[nlev - 1];
return(lapl);
}
/// <summary>
/// Forward Laplacian pyramid transform.
/// </summary>
/// <param name="data">Gaussian pyramid</param>
/// <returns>Pyramid</returns>
public Complex32[][] Forward(Complex32[][] data)
{
int nlev = data.Length;
Complex32[][] lapl = new Complex32[nlev][];
for (int i = 1; i < nlev; i++)
{
lapl[i - 1] = GaussianPyramidTransform.sub(data[i - 1], GaussianPyramidTransform.upsample(data[i], this.radius));
}
lapl[nlev - 1] = data[nlev - 1];
return(lapl);
}
// **************************************************
// Laplacian Pyramid Transform
// **************************************************
// ORIGINALS: Burt, P., and Adelson, E. H.
// IEEE Transactions on Communication, COM-31:532-540
// (1983).
// Designed by Valery Asiryan (c), 2015-2020
// Moscow, Russia.
// **************************************************
/// <summary>
/// Forward Laplacian pyramid transform.
/// </summary>
/// <param name="data">Matrix</param>
/// <returns>Pyramid</returns>
public float[][,] Forward(float[,] data)
{
int r = data.GetLength(0), c = data.GetLength(1);
int nlev = (int)Math.Min((Math.Log(Math.Min(r, c)) / Math.Log(2)), levels);
float[][,] lapl = new float[nlev][, ];
float[,] I, J = data;
for (int i = 0; i < nlev - 1; i++)
{
I = GaussianPyramidTransform.downsample(J, this.radius);
lapl[i] = GaussianPyramidTransform.sub(J, GaussianPyramidTransform.upsample(I, this.radius));
J = I;
}
lapl[nlev - 1] = J;
return(lapl);
}
/// <summary>
/// Forward Laplacian pyramid transform.
/// </summary>
/// <param name="data">Array</param>
/// <returns>Pyramid</returns>
public Complex32[][] Forward(Complex32[] data)
{
int r = data.Length;
int nlev = (int)Math.Min((Math.Log(r) / Math.Log(2)), levels);
Complex32[][] lapl = new Complex32[nlev][];
Complex32[] I, J = data;
for (int i = 0; i < nlev - 1; i++)
{
I = GaussianPyramidTransform.downsample(J, this.radius);
lapl[i] = GaussianPyramidTransform.sub(J, GaussianPyramidTransform.upsample(I, this.radius));
J = I;
}
lapl[nlev - 1] = J;
return(lapl);
}