/// <summary>
/// Assumes the passed matrix is a spectrogram. i.e. rows=frames, cols=freq bins.
/// WARNING: This method should NOT be used for short recordings (i.e LT approx 10-15 seconds long)
/// because it obtains a background noise profile from the passed percentile of lowest energy frames.
///
/// Same method as above except take square root of the cell energy divided by the noise.
/// Taking the square root has the effect of reducing image contrast.
/// </summary>
public static double[,] NoiseReduction_byDivisionAndSqrRoot(double[,] matrix, int percentileThreshold)
{
double[] profile = NoiseProfile.GetNoiseProfile_fromLowestPercentileFrames(matrix, percentileThreshold);
profile = DataTools.filterMovingAverage(profile, 3);
// to prevent division by zero.
double epsilon = 0.0001;
int rowCount = matrix.GetLength(0);
int colCount = matrix.GetLength(1);
double[,] outM = new double[rowCount, colCount]; //to contain noise reduced matrix
// for all cols i.e. freq bins
for (int col = 0; col < colCount; col++)
{
double denominator = profile[col];
if (denominator < epsilon)
{
denominator = epsilon;
}
// for all rows
for (int y = 0; y < rowCount; y++)
{
outM[y, col] = Math.Sqrt(matrix[y, col] / denominator);
} //end for all rows
} //end for all cols
return(outM);
}
/// <summary>
/// Assumes the passed matrix is a spectrogram. i.e. rows=frames, cols=freq bins.
/// WARNING: This method should NOT be used for short recordings (i.e LT approx 10-15 seconds long)
/// Obtains a background noise profile from the passed percentile of lowest energy frames,
/// Then subtracts the noise profile value from every cell.
/// This method was adapted from a paper by Briggs.
/// </summary>
/// <param name="matrix"></param>
/// <param name="percentileThreshold"></param>
/// <returns></returns>
public static double[,] NoiseReduction_byLowestPercentileSubtraction(double[,] matrix, int percentileThreshold)
{
double[] profile = NoiseProfile.GetNoiseProfile_fromLowestPercentileFrames(matrix, percentileThreshold);
profile = DataTools.filterMovingAverage(profile, 3);
int rowCount = matrix.GetLength(0);
int colCount = matrix.GetLength(1);
double[,] outM = new double[rowCount, colCount]; //to contain noise reduced matrix
for (int col = 0; col < colCount; col++) //for all cols i.e. freq bins
{
for (int y = 0; y < rowCount; y++) //for all rows
{
outM[y, col] = matrix[y, col] - profile[col];
} //end for all rows
} //end for all cols
return(outM);
}