/// <summary>
/// Compress a 3D matrix
/// </summary>
/// <param name="data_input">data matrix</param>
/// <param name="level">number of wavelet levels</param>
/// <param name="threshold">threshold where all absolute values less than this is set to zero</param>
public static void Compress3D(double[][][] data_input, int level, int threshold)
{
int temp_level = level;
int ex_length = data_input[0][0].Length;
int ex_width = data_input[0].Length;
int ex_height = data_input.Length;
int temp_ex_length = ex_length;
int temp_ex_width = ex_width;
int temp_ex_height = ex_height;
while (temp_level > 0 && ex_length > 1 && ex_width > 1 && ex_height > 1)
{
HaarWaveletTransform.HaarTransform3D(data_input, ex_length, ex_width, ex_height);
if (ex_length > 1)
{
ex_length = ex_length / 2;
}
if (ex_width > 1)
{
ex_width = ex_width / 2;
}
if (ex_height > 1)
{
ex_height = ex_height / 2;
}
temp_level--;
}
Quantize.DataQuantize3D(data_input, temp_ex_length, temp_ex_width, temp_ex_height, threshold);
}
/// <summary>
/// Compress a 2D matrix
/// </summary>
/// <param name="data_input">data matrix</param>
/// <param name="level">number of wavelet levels</param>
/// <param name="threshold">threshold where all absolute values less than this is set to zero</param>
/// <param name="lastHeight">return last height processed</param>
/// <param name="lastWidth">return last width processed</param>
public static void Compress2D(double[][] data_input, int level, int threshold, out int lastHeight, out int lastWidth, bool doCompression = true)
{
int temp_level = level;
int ex_height = data_input.Length;
int ex_width = data_input[0].Length;
int temp_ex_height = ex_height;
int temp_ex_width = ex_width;
while (temp_level > 0 && ex_height > 1 && ex_width > 1)
{
HaarWaveletTransform.HaarTransform2D(data_input, ex_height, ex_width);
if (ex_width > 1)
{
ex_width = ex_width / 2;
}
if (ex_height > 1)
{
ex_height = ex_height / 2;
}
temp_level--;
}
if (doCompression)
{
Quantize.DataQuantize2D(data_input, temp_ex_height, temp_ex_width, threshold);
}
lastHeight = ex_height;
lastWidth = ex_width;
}
public static void CompressDecompress2D(double[][] data_input, int level, int threshold)
{
int temp_level = level;
int ex_height = data_input.Length;
int ex_width = data_input[0].Length;
int temp_ex_height = ex_height;
int temp_ex_width = ex_width;
while (temp_level > 0 && ex_height > 1 && ex_width > 1)
{
HaarWaveletTransform.HaarTransform2D(data_input, ex_height, ex_width);
if (ex_width > 1)
{
ex_width = ex_width / 2;
}
if (ex_height > 1)
{
ex_height = ex_height / 2;
}
temp_level--;
}
Quantize.DataQuantize2D(data_input, temp_ex_height, temp_ex_width, threshold);
while (temp_level < level && ex_height > 1 && ex_width > 1)
{
if (ex_width > 1)
{
ex_width = ex_width * 2;
}
if (ex_height > 1)
{
ex_height = ex_height * 2;
}
HaarWaveletTransform.InverseHaarTransform2D(data_input, ex_height, ex_width);
temp_level++;
}
}
public static void CompressDecompress(string file_input, string file_output, int level, int value)
{
int i = 0;
int j = 0;
int k = 0;
int lon = 0;
int wid = 0;
int hei = 0;
int temp_ex_lon = 0;
int temp_ex_wid = 0;
int temp_ex_hei = 0;
int ex_lon = 0;
int ex_wid = 0;
int ex_hei = 0;
int temp;
int temp_level = level;
double mse = 0;
double psnr = 0;
int file_size = 0;
double[] file_in = new double[file_size];
double[] file_out = new double[file_size];
// Load file data into data_input[j][k][i]
double[][][] data_input = new double[j][][];
while (temp_level > 0 && ex_lon > 1 && ex_wid > 1 && ex_hei > 1)
{
HaarWaveletTransform.HaarTransform3D(data_input, ex_lon, ex_wid, ex_hei);
if (ex_lon > 1)
{
ex_lon = ex_lon / 2;
}
if (ex_wid > 1)
{
ex_wid = ex_wid / 2;
}
if (ex_hei > 1)
{
ex_hei = ex_hei / 2;
}
temp_level--;
}
Quantize.DataQuantize3D(data_input, temp_ex_lon, temp_ex_wid, temp_ex_hei, value);
while (temp_level < level && ex_lon > 1 && ex_wid > 1 && ex_hei > 1)
{
if (ex_lon > 1)
{
ex_lon = ex_lon * 2;
}
if (ex_wid > 1)
{
ex_wid = ex_wid * 2;
}
if (ex_hei > 1)
{
ex_hei = ex_hei * 2;
}
HaarWaveletTransform.InverseHaarTransform3D(data_input, ex_lon, ex_wid, ex_hei);
temp_level++;
}
file_out = new double[file_size];
for (i = 0; i < hei; i++)
{
for (j = 0; j < lon; j++)
{
for (k = 0; k < wid; k++)
{
temp = lon * wid * i + wid * j + k;
file_out[temp] = data_input[j][k][i];
}
}
}
mse = VerificationResult.MeanSquaredError(file_in, file_out, ref file_size);
psnr = VerificationResult.PeakSignalToNoiseRatio(mse);
Console.Write("MSE: ");
Console.Write(mse);
Console.Write("\n");
Console.Write("PSNR: ");
Console.Write(psnr);
Console.Write("\n");
// save file file_out to file_output with file_size
file_in = null;
file_out = null;
data_input = null;
}
