public Image RunFilter(Image src)
{
filterDataContext db = new filterDataContext();
//Bilateral Bilateral = new Bilateral();
double[] sigma = new double[] { 3, 0.1 };
double w = 5;
MWNumericArray mw_sigma = new MWNumericArray(sigma);
//MWArray Result = Bilateral.bfilter2(image, w, mw_sigma);
//MWArray image = new MWNumericArray(src.Array.Array);
/*
int H = src.Height;
int W = src.Width;
int sq = W * H;
*/
MWArray[] Result = bilateral(2, src.image, w, mw_sigma);
//MWArray[] Result = bfilter2(2, src.image, w, mw_sigma);
MWNumericArray descriptor = null;
descriptor = (MWNumericArray)Result[0];
double[,] result = null;
result = (double[,])descriptor.ToArray(MWArrayComponent.Real);
Image res = new Image(result);
MWNumericArray e_descriptor = null;
e_descriptor = (MWNumericArray)Result[1];
WorkTime = (double)e_descriptor.ToScalarDouble();
db.add_b_res(src.Height, src.Height / src.Width, WorkTime, w, sigma[0], sigma[1]);
Result = null;
e_descriptor = null;
result = null;
mw_sigma = null;
GC.Collect();
return res;
}
public static void Analyze(System.ComponentModel.BackgroundWorker worker)
{
int i = 0;
foreach (string file in Directory.GetFiles("C:\\Users\\Forpatril\\Documents\\Visual Studio 2010\\Projects\\Diploma_cs\\Images", "*.jpg"))
{
Image img = new Image(file);
for (int w = 2; w < 35; w++)
for (int sig = 1; sig < w / 2; sig++)
{
filterclass fc = new filterclass();
Noise n = new Noise();
Image img_n = n.addNoise("gaussian", img, 0, 0.055);
double[] p = new double[] {w, sig, 0.2};
MWNumericArray parameters = new MWNumericArray(p);
MWLogicalArray mw_print = new MWLogicalArray(Form1.print);
MWArray[] Result = fc.filter2(2, img_n.image, "bilateral", parameters, mw_print);
MWNumericArray descriptor = null;
descriptor = (MWNumericArray)Result[0];
double[,] result = null;
result = (double[,])descriptor.ToArray(MWArrayComponent.Real);
Image ret = new Image(result);
MWNumericArray e_descriptor = null;
e_descriptor = (MWNumericArray)Result[1];
ret.Time = (double)e_descriptor.ToScalarDouble();
filterDataContext db = new filterDataContext();
psnrClass ps = new psnrClass();
double psnr = (double)((MWNumericArray)ps.psnr(ret.image, img.image)).ToScalarDouble();
db.add_line("bilateral", "gaussian", img.Height, img.Width, ret.Time, psnr, p[0], p[1], p[2]);
Result = null;
e_descriptor = null;
result = null;
parameters = null;
img_n = null;
n = null;
descriptor = null;
ret = null;
ps = null;
fc = null;
GC.Collect();
}
worker.ReportProgress(i++);
img = null;
GC.Collect();
}
}
public static void Fill(string path, int id, System.ComponentModel.BackgroundWorker worker)
{
int i = 0;
foreach (string file in Directory.GetFiles(path, "*.jpg"))
{
filterDataContext db = new filterDataContext();
Image img = new Image(file);
Noise n = new Noise();
img = n.addNoise("gaussian", img, 0, 0.055);
RunFilter rf = new RunFilter();
Image ret = rf.Do(img, id);
psnrClass ps = new psnrClass();
double psnr = (double)((MWNumericArray)ps.psnr(ret.image, img.image)).ToScalarDouble();
db.add_line(Filters.type[id],"gaussian",img.Height,img.Width,ret.Time,psnr,Form1.pars.par[id][0],Form1.pars.par[id][1],Form1.pars.par[id][2]);
worker.ReportProgress(i++);
}
}
public Image RunFilter(Image src)
{
filterDataContext db = new filterDataContext();
//Bilateral Bilateral = new Bilateral();
//double[] sigma = new double[] { 3, 0.1 };
//double w = 5;
//MWNumericArray mw_sigma = new MWNumericArray(sigma);
//MWArray Result = Bilateral.bfilter2(image, w, mw_sigma);
//MWNumericArray image = new MWNumericArray(src.Array.Array);
MWArray[] Result = high(2, src.image);//Bilateral.bfilter2(2, image, w, mw_sigma);
Image res = new Image((double[,])((MWNumericArray)Result[0]).ToArray(MWArrayComponent.Real));
MWNumericArray e_descriptor = null;
e_descriptor = (MWNumericArray)Result[1];
WorkTime = (double)e_descriptor.ToScalarDouble();
db.add_h_res(src.Height, src.Height / src.Width, WorkTime, 0.15);
Result = null;
e_descriptor = null;
GC.Collect();
return res;
/*
ihpf ihpf = new ihpf();
Stopwatch stopwatch = new Stopwatch();
stopwatch.Start();
MWArray Result = ihpf.high(image);
stopwatch.Stop();
MWNumericArray descriptor = null;
descriptor = (MWNumericArray)Result;
Bitmap Image;
double[,] d_descriptor = (double[,])descriptor.ToArray(MWArrayComponent.Real);
Image = getImage(d_descriptor);
Graphics g = pictureBox1.CreateGraphics();
g.DrawImage(Image, 1, 1);
label1.Text = stopwatch.Elapsed.ToString();
isColor = false;
db.add_h_res(Image.Height, Image.Height / Image.Width, stopwatch.ElapsedMilliseconds, 0.15);
*/
}
public GraphPane Draw(GraphPane pane, int id)
{
filterDataContext db = new filterDataContext();
double t_max = (double)(from a in db.Datas where (a.ftype == type[id]) && (a.ftype == "gaussian") select a.p_time).Max();
double t_min = (double)(from a in db.Datas where (a.ftype == type[id]) && (a.ftype == "gaussian") select a.p_time).Min();
double p_max = (double)(from a in db.Datas where (a.ftype == type[id]) && (a.ftype == "gaussian") select a.psnr).Max();
double p_min = (double)(from a in db.Datas where (a.ftype == type[id]) && (a.ftype == "gaussian") select a.psnr).Min();
double w_max = (double)(from a in db.Datas where (a.ftype == type[id]) && (a.ftype == "gaussian") select a.p1).Max();
double w_min = (double)(from a in db.Datas where (a.ftype == type[id]) && (a.ftype == "gaussian") select a.p1).Min();
pane.Title.Text = "Анализ продолжительности вычислений";
pane.CurveList.Clear();
pane.YAxis.Scale.Min = p_min;
pane.YAxis.Scale.Max = p_max;
pane.YAxis.Title.Text = "PSNR";
pane.XAxis.Title.Text = "Время обработки";
pane.XAxis.Scale.Min = t_min;
pane.XAxis.Scale.Max = t_max;
pane.Y2Axis.Scale.Min = w_min;
pane.Y2Axis.Scale.Max = w_max;
pane.Y2Axis.Title.Text = "Размер окна фильтра";
PointPairList List1 = new PointPairList();
PointPairList List2 = new PointPairList();
var query = from a in db.Datas where (a.ftype == type[id]) && (a.ftype == "gaussian") select a;
foreach (var test in query)
{
List1.Add((double)test.p_time, (double)test.psnr);
List2.Add((double)test.p_time, (double)test.p1);
}
LineItem Curve1 = pane.AddCurve("", List1, Color.Blue, SymbolType.None);
LineItem Curve2 = pane.AddCurve("", List2, Color.Blue, SymbolType.None);
return pane;
}
public Image RunFilter(Image src, int id)
{
filterDataContext db = new filterDataContext();
double[] p = new double[Form1.pars.par[id].Length];
p = Form1.pars.par[id];
MWNumericArray parameters = new MWNumericArray(p);
MWLogicalArray mw_print = new MWLogicalArray(Form1.print);
MWArray[] Result = filter2(2, src.image, type[id], parameters, mw_print);
MWNumericArray descriptor = null;
descriptor = (MWNumericArray)Result[0];
double[,] result = null;
result = (double[,])descriptor.ToArray(MWArrayComponent.Real);
Image res = new Image(result);
MWNumericArray e_descriptor = null;
e_descriptor = (MWNumericArray)Result[1];
res.Time = WorkTime = (double)e_descriptor.ToScalarDouble();
//db.add_b_res(src.Height, src.Height / src.Width, WorkTime, w, sigma[0], sigma[1]);
Result = null;
e_descriptor = null;
result = null;
parameters = null;
GC.Collect();
return res;
}
public Form1()
{
InitializeComponent();
label1.Text = "";
label2.Text = "";
label3.Text = "";
tabControl1.SelectTab(tabPage2);
run = new bool[] { false, false, false };
im = new List<Image>(11);
pb_array = new List<PictureBox>();
pb_array.Add(pictureBox3);
pb_array.Add(pictureBox4);
pb_array.Add(pictureBox5);
pb_array.Add(pictureBox6);
pb_array.Add(pictureBox7);
pb_array.Add(pictureBox8);
pb_array.Add(pictureBox9);
pb_array.Add(pictureBox11);
pb_array.Add(pictureBox12);
pb_array.Add(pictureBox13);
pb_array.Add(pictureBox14);
pb_array.Add(pictureBox15);
pb_array.Add(pictureBox16);
pb_array.Add(pictureBox17);
pb_array.Add(pictureBox18);
pb_array.Add(pictureBox19);
pb_array.Add(pictureBox20);
pb_array.Add(pictureBox21);
pb_array.Add(pictureBox22);
comboBox1.SelectedIndex = 0;
comboBox2.SelectedIndex = 1;
comboBox3.SelectedIndex = 0;
par = new List<param>(7);
par.Add(new param(0, 0.055));
par.Add(new param(0, 0.055));
par.Add(new param(0.04, 0.04));
par.Add(new param(0.6, 0.25));
par.Add(new param(0, 0.055));
par.Add(new param(12.6, 0.055));
par.Add(new param(12.6, 3));
pars = new Parameters();
npars = new NoiseParameters();
psnr = new double[11];
lb_array = new List<System.Windows.Forms.Label>();
lb_array.Add(label17);
lb_array.Add(label18);
lb_array.Add(label19);
lb_array.Add(label20);
lb_array.Add(label21);
lb_array.Add(label22);
lb_array.Add(label23);
lb_array.Add(label24);
lb_array.Add(label25);
lb_array.Add(label26);
lb_array.Add(label27);
lb_array.Add(label28);
lb_array.Add(label29);
lb_array.Add(label30);
lb_array.Add(label31);
lb_array.Add(label32);
lb_array.Add(label33);
lb_array.Add(label34);
db = new filterDataContext();
}
/*
private Bitmap getImage(double[,] image)
{
int w = image.GetLength(1);
int h = image.GetLength(0);
Bitmap r_image = new Bitmap(w, h);
for (int i = 0; i < h; i++)
{
for (int j = 0; j < w; j++)
{
byte pixel = (byte)(image[i, j] * 255);
Color color = Color.FromArgb(255, pixel, pixel, pixel);
r_image.SetPixel(j, i, color);
}
}
return r_image;
}
private Bitmap getImage(double[, ,] image)
{
int w = image.GetLength(2);
int h = image.GetLength(1);
Bitmap r_image = new Bitmap(w, h);
for (int i = 0; i < h; i++)
{
for (int j = 0; j < w; j++)
{
byte r = (byte)(image[0, i, j] * 255);
byte g = (byte)(image[1, i, j] * 255);
byte b = (byte)(image[2, i, j] * 255);
Color color = Color.FromArgb(255, r, g, b);
r_image.SetPixel(j, i, color);
}
}
return r_image;
}
*/
private void button3_Click(object sender, EventArgs e)
{
B b = new B();
Noise n = new Noise();
Image res = n.addNoise("gaussian", image, 0, 0.055);
pictureBox1.Image = res.Bitmap;
Application.DoEvents();
res = b.RunFilter(res);
//Bilateral Bilateral = new Bilateral();
//double[] sigma = new double[] {3, 0.1};
//double w = 5;
//MWNumericArray mw_sigma = new MWNumericArray(sigma);
//Stopwatch stopwatch = new Stopwatch();
//stopwatch.Start();
////MWArray Result = Bilateral.bfilter2(image, w, mw_sigma);
//MWArray[] Result = Bilateral.bfilter2(2, image, w, mw_sigma);
//stopwatch.Stop();
//MWNumericArray descriptor = null;
//descriptor = (MWNumericArray)Result[0];
//MWNumericArray e_descriptor = null;
//e_descriptor = (MWNumericArray)Result[1];
//double Elapsed = (double)e_descriptor.ToScalarDouble();
//Bitmap Image;
//if (!isColor)
//{
// double[,] d_descriptor = (double[,])descriptor.ToArray(MWArrayComponent.Real);
// Image = getImage(d_descriptor);
//}
//else
//{
// double[,,] d_descriptor = (double[, ,])descriptor.ToArray(MWArrayComponent.Real);
// Image = getImage(d_descriptor);
//}
//pictureBox1.Size.Height = res.Height;
//pictureBox1.Size.Width = res.Width;
pictureBox1.Image = res.Bitmap;
//label1.Text = stopwatch.Elapsed.ToString();
//label2.Text = Elapsed.ToString();
filterDataContext db = new filterDataContext();
label1.Text = b.WorkTime.ToString();
db.add_b_res(res.Height, res.Height / res.Width, b.WorkTime, 5, 3, 0.1);
//isColor = false;
b = null;
n = null;
res = null;
GC.Collect();
}
public Image RunFilter(Image src)
{
filterDataContext db = new filterDataContext();
double[] sigma = new double[] { 3.0, 3.0 };
MWNumericArray mw_sigma = new MWNumericArray(sigma);
MWLogicalArray mw_print = new MWLogicalArray(Form1.print);
MWArray[] Result = filter2(2, src.image, type[2], mw_print);//spfilt(2, src.image, "median");
MWNumericArray descriptor = null;
descriptor = (MWNumericArray)Result[0];
double[,] result = null;
result = (double[,])descriptor.ToArray(MWArrayComponent.Real);
Image res = new Image(result);
MWNumericArray e_descriptor = null;
e_descriptor = (MWNumericArray)Result[1];
WorkTime = (double)e_descriptor.ToScalarDouble();
//db.add_b_res(src.Height, src.Height / src.Width, WorkTime, w, sigma[0], sigma[1]);
Result = null;
e_descriptor = null;
result = null;
mw_sigma = null;
GC.Collect();
return res;
}
