static Histogram ComputeChannelHistogram(IplImage channel)
{
var histogram = new Histogram(1, new[] { 256 }, HistogramType.Array, new[] { new[] { 0, 256f } });
histogram.CalcArrHist(new[] { channel });
histogram.Normalize(1);
return(histogram);
}
public void Normalize_UniformHistogram_SumOfBinsEqualsOne()
{
var factor = 1.0;
var hist = new Histogram(1, new[] { 100 }, HistogramType.Array, new[] { new[] { 0, 256f } });
var diag = Mat.Eye(50, 50, Depth.U8, 1);
hist.CalcArrHist(new[] { diag });
hist.Normalize(factor);
var sum = CV.Sum(hist.Bins).Val0;
Assert.AreEqual(factor, sum);
}
public Histogram CummulativeHistogram()
{
var histogram = new Histogram(256, new[] { 0, 256 }, HistogramType.Array);
histogram.CalcArrHist(new[] { GradientMap });
histogram.Normalize(1.0);
var cummulative = histogram.Bins.GetReal(0);
for (var index = 1; index < 256; index++)
{
cummulative += histogram.Bins.GetReal(index);
histogram.Bins.SetReal(index, cummulative);
}
return(histogram);
}
public IObservable <Mat> Process <TArray>(IObservable <TArray> source) where TArray : Arr
{
return(Observable.Defer(() =>
{
var histogram = new Histogram(1, new[] { Bins }, HistogramType.Array, new[] { new[] { Min, Max } });
histogram.Clear();
return source.Select(input =>
{
histogram.CalcArrHist(new[] { input }, Accumulate);
if (Normalize)
{
histogram.Normalize(1);
}
var output = histogram.Bins.GetMat(true).Reshape(0, 1);
return output.Clone();
});
}));
}
