void PlotBoxR()
{
var plotGauss = new PlotModel {
Title = $"Box R for {fileInfo.Name}"
};
plotGauss.Axes.Add(new LinearAxis {
Title = "R", Position = AxisPosition.Bottom
});
plotGauss.Axes.Add(new LinearAxis {
Title = "PSNR", Position = AxisPosition.Left
});
using (var imageLoader = new ImageLoader())
{
imageLoader.Load(fileInfo.FullName);
Image image = imageLoader.Image;
var points = new LineSeries
{
StrokeThickness = 2,
MarkerSize = 4,
Color = OxyColors.Red
};
for (var R = 1; R <= 8; R++)
{
//imageLoader.Image = noise;
imageLoader.AddNoise(new GaussNoise(new Normal(0, 50))); // 100 dispersy
imageLoader.AddBoxFilter(R);
double psnr = imageLoader.CalculatePSNR(image);
points.Points.Add(new DataPoint(R, psnr));
imageLoader.Image = image;
}
plotGauss.Series.Add(points);
}
pngExporter.ExportToFile(plotGauss, $"{outputPath}/{fileInfo.Name}/BoxFilterPlotR.png");
}
private static void BoxFilter(FileInfo file, string outputFileName)
{
Console.WriteLine("***BOX FILTER***");
if (file == null)
{
throw new ArgumentNullException(nameof(file));
}
using (var imageLoader = new ImageLoader())
{
imageLoader.Load(file.FullName);
Image image = imageLoader.Image;
imageLoader.AddNoise(new GaussNoise(new Normal(0, 0.25)));
imageLoader.Save($"{outputFileName}noise{file.Extension}");
Console.WriteLine($"psnr-noise: {imageLoader.CalculatePSNR(image):F2}");
imageLoader.AddBoxFilter(5);
imageLoader.Save($"{outputFileName}boxfiltered{file.Extension}");
Console.WriteLine($"psnr-boxfilter: {imageLoader.CalculatePSNR(image):F2}");
}
}
