public static void TestDenoise(string imageInPath) {
// Read Image
Image img = Image.FromFile(imageInPath);
Bitmap bmp = new Bitmap(img);
double[][] image = new double[bmp.Height][];
for (int i = 0; i < bmp.Height; i++)
{
image[i] = new double[bmp.Width];
for (int j = 0; j < bmp.Width; j++) {
//image[i][j] = bmp.GetPixel(j, i).ToArgb();
image[i][j] = bmp.GetPixel(j, i).B; // use only blue channel
}
}
//Matrix imageMatrix = new Matrix(image);
//imageMatrix.WriteCSV("lena-blue.csv", ";");
// Normalize the pixel values to the range 0..1.0. It does this by dividing all pixel values by the max value.
double max = image.Max((b) => b.Max((v) => Math.Abs(v)));
double[][] imageNormalized = image.Select(i => i.Select(j => j/max).ToArray()).ToArray();
Matrix normalizedMatrix = new Matrix(imageNormalized);
//normalizedMatrix.WriteCSV("lena-normalized.csv", ";");
normalizedMatrix.DrawMatrixImage("lena-original.png", -1, -1, false);
// Add Noise using normally distributed pseudorandom numbers
// image_noisy = image_normalized + 0.1 * randn(size(image_normalized));
TestSimpleRNG.SimpleRNG.SetSeedFromSystemTime();
double[][] imageNoisy = imageNormalized.Select(i => i.Select(j => j + (0.1 * TestSimpleRNG.SimpleRNG.GetNormal())).ToArray()).ToArray();
Matrix matrixNoisy = new Matrix(imageNoisy);
matrixNoisy.DrawMatrixImage("lena-noisy.png", -1, -1, false);
// Haar Wavelet Transform
Matrix haarMatrix = HaarWaveletTransform(imageNoisy);
// Thresholding
double threshold = 0.15; // 0.15 seems to work well with the noise added above, 0.1
double[][] yHard = Thresholding.perform_hard_thresholding(haarMatrix.MatrixData, threshold);
double[][] ySoft = Thresholding.perform_soft_thresholding(haarMatrix.MatrixData, threshold);
double[][] ySemisoft = Thresholding.perform_semisoft_thresholding(haarMatrix.MatrixData, threshold, threshold*2);
double[][] ySemisoft2 = Thresholding.perform_semisoft_thresholding(haarMatrix.MatrixData, threshold, threshold*4);
double[][] yStrict = Thresholding.perform_strict_thresholding(haarMatrix.MatrixData, 10);
// Inverse 2D Haar Wavelet Transform
Matrix zHard = InverseHaarWaveletTransform(yHard);
Matrix zSoft = InverseHaarWaveletTransform(ySoft);
Matrix zSemisoft = InverseHaarWaveletTransform(ySemisoft);
Matrix zSemisoft2 = InverseHaarWaveletTransform(ySemisoft2);
Matrix zStrict = InverseHaarWaveletTransform(yStrict);
//zHard.WriteCSV("lena-thresholding-hard.csv", ";");
// Output the images
zHard.DrawMatrixImage("lena-thresholding-hard.png", -1, -1, false);
zSoft.DrawMatrixImage("lena-thresholding-soft.png", -1, -1, false);
zSemisoft.DrawMatrixImage("lena-thresholding-semisoft.png", -1, -1, false);
zSemisoft2.DrawMatrixImage("lena-thresholding-semisoft2.png", -1, -1, false);
zStrict.DrawMatrixImage("lena-thresholding-strict.png", -1, -1, false);
}