public void ProcessImageTest()
{
double[,] diag = Matrix.Magic(5);
Bitmap input;
new MatrixToImage().Convert(diag, out input);
// Create a new Variance filter
Variance filter = new Variance();
// Apply the filter
Bitmap output = filter.Apply(input);
double[,] actual;
new ImageToMatrix().Convert(output, out actual);
string str = actual.ToString(CSharpMatrixFormatProvider.InvariantCulture);
double[,] expected =
{
{ 0, 0, 0, 0, 0 },
{ 0.0941176470588235, 0.545098039215686, 0.396078431372549, 0.376470588235294, 0.192156862745098 },
{ 0.298039215686275, 0.376470588235294, 0.27843137254902, 0.211764705882353, 0.133333333333333 },
{ 0.317647058823529, 0.203921568627451, 0.2, 0.16078431372549, 0.109803921568627 },
{ 0.0509803921568627, 0.109803921568627, 0.16078431372549, 0.2, 0.203921568627451 }
};
Assert.IsTrue(expected.IsEqual(actual, 1e-6));
}
public void VarianceTest1()
{
Bitmap image = Accord.Imaging.Image.Clone(Properties.Resources.lena512);
Variance variance = new Variance();
Bitmap result = variance.Apply(image);
Assert.IsNotNull(result);
}
public void VarianceTest1()
{
Bitmap image = Properties.Resources.lena512;
Variance variance = new Variance();
Bitmap result = variance.Apply(image);
Assert.IsNotNull(result);
}
private void SetFilter()
{
if (fast)
{
ImageType = ImageTypes.Rgb24bpp;
Af.FastVariance newFilter = new Af.FastVariance();
newFilter.Radius = radius;
imageFilter = newFilter;
}
else
{
ImageType = ImageTypes.Rgb24bpp;
Af.Variance newFilter = new Af.Variance();
newFilter.Radius = radius;
imageFilter = newFilter;
}
}
