/// <summary>
///
/// </summary>
/// <param name="image"></param>
/// <returns></returns>
public override Image Apply(Image image)
{
GetParams(fm);
if (!(image is Image))
{
return(image);
}
Bitmap dst = AddinUtils.CloneImage(image) as Bitmap;
SharpenMode sharpenMode = (SharpenMode)Params["SharpenMode"].Value;
double gaussianSigma = (double)Params["GaussianSigma"].Value;
int gaussianSize = (int)Params["GaussianSize"].Value;
int gaussianThreshold = (int)Params["GaussianThreshold"].Value;
float gdiRatio = (float)Params["GdiRatio"].Value;
float gdiAmount = (float)Params["GdiAmount"].Value;
Accord.Imaging.Filters.IFilter filter = null;
switch (sharpenMode)
{
case SharpenMode.Normal:
filter = new Accord.Imaging.Filters.Sharpen();
dst = (filter as Accord.Imaging.Filters.Sharpen).Apply(dst);
break;
case SharpenMode.Gaussian:
filter = new Accord.Imaging.Filters.GaussianSharpen();
(filter as Accord.Imaging.Filters.GaussianSharpen).Sigma = gaussianSigma;
(filter as Accord.Imaging.Filters.GaussianSharpen).Size = gaussianSize;
(filter as Accord.Imaging.Filters.GaussianSharpen).Threshold = gaussianThreshold;
dst = filter.Apply(dst);
break;
case SharpenMode.GDI:
var effect = new SharpenEffect(gdiRatio, gdiAmount);
dst.ApplyEffect(effect, new Rectangle(0, 0, dst.Width, dst.Height));
break;
}
AddinUtils.CloneExif(image, dst);
return(dst);
}
public rettype runalgo(string s)
{
string dupImagePath = s;
Bitmap org0 = (Bitmap)Accord.Imaging.Image.FromFile(dupImagePath);
// Bitmap org1 = org0.Clone(System.Drawing.Imaging.PixelFormat.Format24bppRgb);
if (greyscaleenable)
{
Accord.Imaging.Filters.GrayscaleBT709 gr = new Accord.Imaging.Filters.GrayscaleBT709();
org0 = gr.Apply(org0);
}
Bitmap org1 = org0.Clone(System.Drawing.Imaging.PixelFormat.Format24bppRgb);
Accord.Imaging.Filters.Difference filter = new Accord.Imaging.Filters.Difference(org1);
Bitmap noiserem = org1.Clone(System.Drawing.Imaging.PixelFormat.Format24bppRgb);
foreach (string filterid in algorithm)
{
int filterno = getfilter(filterid);
if (filterno == 2)
{
// Console.WriteLine("AdaptiveSmoothing");
Accord.Imaging.Filters.AdaptiveSmoothing noisefilter = new Accord.Imaging.Filters.AdaptiveSmoothing();
noiserem = noisefilter.Apply(noiserem);
}
else if (filterno == 4)
{
// Console.WriteLine("AdditiveNoise");
Accord.Imaging.Filters.AdditiveNoise noisefilter = new Accord.Imaging.Filters.AdditiveNoise();
noiserem = noisefilter.Apply(noiserem);
}
else if (filterno == 3)
{
// Console.WriteLine("BilateralSmoothing");
Accord.Imaging.Filters.BilateralSmoothing noisefilter = new Accord.Imaging.Filters.BilateralSmoothing();
noiserem = noisefilter.Apply(noiserem);
}
if (filterno == 5)
{
//Bitmap gra = new Bitmap(noiserem.Width, noiserem.Height, PixelFormat.Format8bppIndexed);
// Bitmap gra = new bnoiserem.Clone(System.Drawing.Imaging.PixelFormat.form);
// Console.WriteLine("AdaptiveSmoothing");
Accord.Imaging.Filters.Erosion noisefilter = new Accord.Imaging.Filters.Erosion();
noiserem = noisefilter.Apply(noiserem);
}
else if (filterno == 6)
{
// Console.WriteLine("AdditiveNoise");
Accord.Imaging.Filters.Pixellate noisefilter = new Accord.Imaging.Filters.Pixellate();
noiserem = noisefilter.Apply(noiserem);
}
else if (filterno == 7)
{
// Console.WriteLine("BilateralSmoothing");
Accord.Imaging.Filters.GaussianBlur noisefilter = new Accord.Imaging.Filters.GaussianBlur();
noiserem = noisefilter.Apply(noiserem);
}
else if (filterno == 8)
{
// Console.WriteLine("BilateralSmoothing");
Accord.Imaging.Filters.GaussianSharpen noisefilter = new Accord.Imaging.Filters.GaussianSharpen();
noiserem = noisefilter.Apply(noiserem);
}
else
{
///donothing
}
}
// apply the filter
Bitmap resultImage = filter.Apply(noiserem);
double mean = 0.0;// histogram.Mean; // mean red value
Accord.Statistics.Visualizations.Histogram histogram = null;;
if (greyscaleenable == false)
{
Accord.Imaging.ImageStatistics statistics = new Accord.Imaging.ImageStatistics(resultImage);
histogram = statistics.Red;
mean = histogram.Mean; // mean red value
}
else
{
Accord.Imaging.Filters.GrayscaleBT709 gr = new Accord.Imaging.Filters.GrayscaleBT709();
resultImage = gr.Apply(resultImage);
Accord.Imaging.ImageStatistics statistics = new Accord.Imaging.ImageStatistics(resultImage);
histogram = statistics.Gray;
mean = histogram.Mean; // mean red value
}
var lbp = new LocalBinaryPattern(blockSize: 3, cellSize: 6);
// Use it to extract descriptors from the Lena image:
var descriptors = lbp.ProcessImage(resultImage);
double av = 0.0;
foreach (var d in descriptors)
{
av = av + d.Average();
}
av = av / descriptors.Count;
rettype ret = new rettype();
ret.histogram = histogram;
ret.lbpavg = av;
ret.histoavg = mean;
return(ret);
}
