public int Otsu(GrayPixelHistogram[] histogram)
{
//def
Probability[] _pixelProbability = new Probability[_maxPixelValue];
Variance[] _thresholdVariance = new Variance[_maxPixelValue];
Variance _threshold = new Variance();
for (int i = 0; i < _maxPixelValue; i++)
{
_pixelProbability[i] = new Probability();
_thresholdVariance[i] = new Variance();
}
int _counter = 0;
double _objectProbability = 0;
double _groundProbability = 0;
double _objectAverage = 0;
double _groundAverage = 0;
//int _threshold = 0;
//calculate probability for each pixel and store data
foreach (var item in histogram)
{
_pixelProbability[_counter].pixel = item.Value;
_pixelProbability[_counter].probability = ((double)item.Count / (double)_imageSize);
//Console.WriteLine((float)item.Count / (float)_imageSize);
_counter++;
}
//for each threshold -> t
for (int t = 0; t < _maxPixelValue; t++)
{
_objectProbability = 0;
_groundProbability = 0;
_objectAverage = 0;
_groundAverage = 0;
//calculate probability of object
for (int i = 0; i <= t; i++)
{
_objectProbability += _pixelProbability[i].probability;
}
//calculate probability of ground
for (int i = t + 1; i < _maxPixelValue; i++)
{
_groundProbability += _pixelProbability[i].probability;
}
//calculate average of object
for (int i = 0; i <= t; i++)
{
_objectAverage += (i * _pixelProbability[i].probability / _objectProbability);
}
//calculate average of ground
for (int i = t + 1; i < _maxPixelValue; i++)
{
_groundAverage += (i * _pixelProbability[i].probability / _groundProbability);
}
//calculate viariance for each threshold -> t
_thresholdVariance[t].threshold = t;
_thresholdVariance[t].interViariance = _objectProbability * _groundProbability * (_objectAverage - _groundAverage) * (_objectAverage - _groundAverage);
}
//_threshold = _thresholdVariance.GroupBy(x => x.interViariance).Select(group => group.Where(x => x.interViariance == group.Max(y => y.interViariance))).First();
_threshold = _thresholdVariance.MaxBy(x => x.interViariance);
//GroupBy(x => x.Title).Select(group => group.Where(x => x.Price == group.Max(y => y.Price)).First());
;
return(_threshold.threshold);
}
/// <summary>
/// OTSU算法是由日本学者OTSU于1979年提出的一种对图像进行二值化的高效算法。
/// </summary>
/// <param name="histogram"></param>
/// <returns></returns>
public int Otsu(GrayPixelHistogram[] histogram)
{
//def
Probability[] _pixelProbability = new Probability[_maxPixelValue];
Variance[] _thresholdVariance = new Variance[_maxPixelValue];
Variance _threshold = new Variance();
Bitmap myBitmap = new Bitmap(_sampleImage.Width, _sampleImage.Height);
for (int i = 0; i < _maxPixelValue; i++)
{
_pixelProbability[i] = new Probability();
_thresholdVariance[i] = new Variance();
}
int _counter = 0;
double _objectProbability = 0;
double _groundProbability = 0;
double _objectAverage = 0;
double _groundAverage = 0;
//int _threshold = 0;
//calculate probability for each pixel and store data
foreach (var item in histogram)
{
_pixelProbability[_counter].pixel = item.Value;
_pixelProbability[_counter].probability = ((double)item.Count / (double)_imageSize);
//Console.WriteLine((float)item.Count / (float)_imageSize);
_counter++;
}
//for each threshold -> t
for (int t = 0; t < _maxPixelValue; t++)
{
_objectProbability = 0;
_groundProbability = 0;
_objectAverage = 0;
_groundAverage = 0;
//calculate probability of object
for (int i = 0; i <= t; i++)
{
_objectProbability += _pixelProbability[i].probability;
}
//calculate probability of ground
for (int i = t + 1; i < _maxPixelValue; i++)
{
_groundProbability += _pixelProbability[i].probability;
}
//calculate average of object
for (int i = 0; i <= t; i++)
{
_objectAverage += (i * _pixelProbability[i].probability / _objectProbability);
}
//calculate average of ground
for (int i = t + 1; i < _maxPixelValue; i++)
{
_groundAverage += (i * _pixelProbability[i].probability / _groundProbability);
}
//calculate viariance for each threshold -> t
_thresholdVariance[t].threshold = t;
_thresholdVariance[t].interViariance = _objectProbability * _groundProbability * (_objectAverage - _groundAverage) * (_objectAverage - _groundAverage);
}
//_threshold = _thresholdVariance.GroupBy(x => x.interViariance).Select(group => group.Where(x => x.interViariance == group.Max(y => y.interViariance))).First();
_threshold = _thresholdVariance.MaxBy(x => x.interViariance);
//GroupBy(x => x.Title).Select(group => group.Where(x => x.Price == group.Max(y => y.Price)).First());
;
int j = 0;
for (int Xcount = 0; Xcount < myBitmap.Width; Xcount++)
{
for (int Ycount = 0; Ycount < myBitmap.Height; Ycount++)
{
if (_originalPixels[j].value > _threshold.threshold)
{
myBitmap.SetPixel(Xcount, Ycount, Color.White);
}
else if (_originalPixels[j].value < _threshold.threshold)
{
myBitmap.SetPixel(Xcount, Ycount, Color.Black);
}
j++;
}
}
pictureBoxOtsu.Image = myBitmap;
return(_threshold.threshold);
}
