/// <summary>
/// Calculate mean image of sequene (every pixel contains mean of corresponding pixels values from sequence).
/// </summary>
/// <param name="sequecne">
/// Sequence to calculate mean. Every images have to have same dimensions.
/// </param>
/// <returns>
/// Mean of sequence.
/// </returns>
public static FloatMatrix SequenceMean(IEnumerable<FloatMatrix> sequecne)
{
FloatMatrix result = new FloatMatrix(new DataMatrix<float>(sequecne.First().Dimensions));
int num = 0;
foreach (FloatMatrix bias in sequecne)
{
result.Add(bias);
num++;
}
result.Divide((float)num);
return result;
}
/// <summary>
/// Calculate sum of images in sequene (every pixel contains sum of corresponding pixels values from sequence).
/// </summary>
/// <param name="sequecne">
/// Sequence to calculate sum. Every images have to have same dimensions.
/// </param>
/// <returns>
/// Sum of sequence.
/// </returns>
public static FloatMatrix SequenceSum(IEnumerable<FloatMatrix> sequecne)
{
FloatMatrix result = new FloatMatrix(new DataMatrix<float>(sequecne.First().Dimensions));
foreach (FloatMatrix bias in sequecne)
result.Add(bias);
return result;
}
private FloatMatrix CalcMeanAndShow(IEnumerable<FloatMatrix> source, string title)
{
FloatMatrix result = new FloatMatrix(new DataMatrix<float>(source.First().Dimensions));
int n = 0;
foreach (FloatMatrix image in source)
{
n++;
_imageWindow.ShowImage(image);
_imageWindow.ImgForm.Text = title + " " + n.ToString();
result.Add(image);
Wait(_waitOnCalibrationSource);
}
result.Divide((float)n);
return result;
}
