diff --git a/src/core/transformations/convolution.cpp b/src/core/transformations/convolution.cpp
index 71864b7..af164c6 100644
--- a/src/core/transformations/convolution.cpp
+++ b/src/core/transformations/convolution.cpp
@@ -35,6 +35,9 @@ PNM* Convolution::convolute(math::matrix<float> mask, Mode mode = RepeatEdge)
 
     PNM* newImage = new PNM(width, height, image->format());
 
+
+
+
     qDebug() << Q_FUNC_INFO << "Not implemented yet!";
 
     return newImage;
@@ -50,6 +53,15 @@ const math::matrix<float> Convolution::join(math::matrix<float> A, math::matrix<
 
     qDebug() << Q_FUNC_INFO << "Not implemented yet!";
 
+
+    for(int x = 0;  x < size  ; x++){
+        for(int y = 0;  y < size ; y++){
+            C(x,y) = A(x,y) * B(x,y);
+
+        }
+
+    }
+
     return C;
 }
 
@@ -58,8 +70,22 @@ const float Convolution::sum(const math::matrix<float> A)
 {
     float sum = 0.0;
 
+    int size = A.rowno();
+
+    float t  = 4.0;
+     ;
+    for(int x = 0;  x < (int)  A.size() ; x++){
+
+
+    }
+
+
+
     qDebug() << Q_FUNC_INFO << "Not implemented yet!";
 
+
+
+
     return sum;
 
 }
diff --git a/src/core/transformations/noise_bilateral.cpp b/src/core/transformations/noise_bilateral.cpp
index cc6579f..5db5562 100644
--- a/src/core/transformations/noise_bilateral.cpp
+++ b/src/core/transformations/noise_bilateral.cpp
@@ -21,28 +21,73 @@ PNM* NoiseBilateral::transform()
     sigma_r = getParameter("sigma_r").toInt();
     radius = sigma_d;
 
-    qDebug() << Q_FUNC_INFO << "Not implemented yet!";
+    for(int x  = 0 ; x < width; x++){
+        for (int y = 0 ; y < height; y++) {
+
+           int g = calcVal(x,y, GChannel);
+           int r =  calcVal(x,y, RChannel);
+           int b = calcVal(x,y, BChannel);
+           newImage->setPixel(x,y,QColor(r,g,b).rgba());
+        }
+    }
 
     return newImage;
 }
 
 int NoiseBilateral::calcVal(int x, int y, Channel channel)
 {
-    qDebug() << Q_FUNC_INFO << "Not implemented yet!";
+    double sumNumerator = 0;
+    double sumDenominator = 0;
 
-    return 0;
+    double colorClosenes = 0;
+    double spatialClosennes = 0;
+    int colorValue;
+    int colorValueRef;
+
+    for (  int i = x- radius ; i <= x+radius ; i++) {
+        for (  int j = y- radius ; j <= y+radius ; j++) {
+
+               if ( i+radius >=  image->width() ||
+                    i-radius <  0 ||
+                    j+radius >=  image->height() ||
+                    j-radius <  0 ) {
+                      continue;
+                }
+
+                if (channel==LChannel){
+                    colorValue =  qAlpha(image->pixel(i,j));
+                    colorValueRef =  qAlpha(image->pixel(x,y));
+                }
+                if (channel==RChannel){
+                    colorValue = (qRed(image->pixel(i,j)));
+                    colorValueRef =  qRed(image->pixel(x,y));
+                }
+                if (channel==GChannel){
+                    colorValueRef =  qGreen(image->pixel(x,y));
+                    colorValue =  (qGreen(image->pixel(i,j)));
+                }
+                 if (channel==BChannel){
+                     colorValueRef =  qBlue(image->pixel(x,y));
+                     colorValue =  ( qBlue(image->pixel(i,j)));
+                }
+
+                colorClosenes = colorCloseness(colorValue,colorValueRef);
+                spatialClosennes = spatialCloseness( QPoint(i,j),QPoint(x,y));
+
+                sumNumerator = sumNumerator +( colorValue* colorClosenes * spatialClosennes);
+                sumDenominator =sumDenominator + ( colorClosenes * spatialClosennes);
+
+            }
+        }
+    return sumNumerator/sumDenominator;
 }
 
 float NoiseBilateral::colorCloseness(int val1, int val2)
 {
-    qDebug() << Q_FUNC_INFO << "Not implemented yet!";
-
-    return 0;
+    return exp(-(((val1-val2)^2)/(2*sigma_r^2)));
 }
 
 float NoiseBilateral::spatialCloseness(QPoint point1, QPoint point2)
 {
-    qDebug() << Q_FUNC_INFO << "Not implemented yet!";
-
-    return 0;
+    return exp(-((point1.x() - point2.x())^2 + ( point1.y() - point2.y())^2)/(2*sigma_d^2));
 }
diff --git a/src/core/transformations/noise_median.cpp b/src/core/transformations/noise_median.cpp
index 1d8a9f7..0913853 100644
--- a/src/core/transformations/noise_median.cpp
+++ b/src/core/transformations/noise_median.cpp
@@ -17,16 +17,57 @@ PNM* NoiseMedian::transform()
 
     PNM* newImage = new PNM(width, height, image->format());
 
-    qDebug() << Q_FUNC_INFO << "Not implemented yet!";
+    for(int x  = 0 ; x < width; x++){
+        for (int y = 0 ; y < height; y++) {
 
+           int g = getMedian(x,y, GChannel);
+           int r =  getMedian(x,y, RChannel);
+           int b = getMedian(x,y, BChannel);
+           newImage->setPixel(x,y,QColor(r,g,b).rgba());
+        }
+    }
     return newImage;
 }
 
 int NoiseMedian::getMedian(int x, int y, Channel channel)
 {
     int radius = getParameter("radius").toInt();
+    QSet<int> set;
 
-    qDebug() << Q_FUNC_INFO << "Not implemented yet!";
+    QList<int> list = QList<int>::fromSet(set);
+    std::sort(list.begin(), list.end());
 
-    return 0;
+
+        for (  int i = x- radius ; i <= x+radius ; i++) {
+            for (  int j = y- radius ; j <= y+radius ; j++) {
+
+                if ( i+radius >=  image->width() ||
+                     i-radius <  0 ||
+                     j+radius >=  image->height() ||
+                     j-radius <  0 ) {
+                    continue;
+                }
+
+                if (channel==LChannel)  set.insert(qAlpha(image->pixel(i,j)));
+                if (channel==RChannel)  set.insert(qRed(image->pixel(i,j)));
+                if (channel==GChannel)  set.insert(qGreen(image->pixel(i,j)));
+                if (channel==BChannel)  set.insert( qBlue(image->pixel(i,j)));
+
+            }
+        }
+
+    QList<int> data = QList<int>::fromSet(set);
+    std::sort(data.begin(), data.end());
+    int result =0 ;
+
+    if( data.size() %2 == 1){
+        result  =  data.at(data.size()/2);
+    }else if(data.size()>3){
+        int first_med = data.at((data.size()/2 )-1);
+        int sec_dem = data.at((data.size()/2 ));
+        result =  (first_med+sec_dem)/2;
+    }
+    data.clear();
+    set.clear();
+    return result;
 }