zadanie_10

src/core/transformations/noise_bilateral.cpp

@@ -19,30 +19,58 @@ PNM* NoiseBilateral::transform()
 
     sigma_d = getParameter("sigma_d").toInt();
     sigma_r = getParameter("sigma_r").toInt();
-    radius = sigma_d;
+    radius = sigma_d * 2;
 
-    qDebug() << Q_FUNC_INFO << "Not implemented yet!";
+    for (int x=0;x<width;++x) {
+        for (int y=0;y<height;++y) {
+            int r = calcVal(x,y, RChannel);
+            int g = calcVal(x,y, GChannel);
+            int b = calcVal(x,y, BChannel);
+            newImage->setPixel(x, y, QColor(r,g,b).rgb());
+        }
+    }
 
     return newImage;
 }
 
 int NoiseBilateral::calcVal(int x, int y, Channel channel)
 {
-    qDebug() << Q_FUNC_INFO << "Not implemented yet!";
+    math::matrix<float> window = getWindow(x, y, radius, channel, RepeatEdge);
 
-    return 0;
+    int pixel = image->pixel(x,y);
+
+    switch (channel) {
+      case RChannel: pixel = qRed(pixel);
+      case GChannel: pixel = qGreen(pixel);
+      case BChannel: pixel = qBlue(pixel);
+    }
+
+    float sum1 = 0;
+    float sum2 = 0;
+
+    for (int i=0;i<radius;++i) {
+        for (int j=0;j<radius;++j) {
+            int pixelVal = window[i][j];
+            QPoint point1((i - radius/2) + x, (j - radius/2) + y);
+            QPoint point2(x,y);
+            sum1 += pixelVal * colorCloseness(pixelVal, pixel) * spatialCloseness(point1, point2);
+            sum2 += colorCloseness(pixelVal, pixel) * spatialCloseness(point1, point2);
+        }
+    }
+
+    return sum2 != 0 ? sum1 / sum2 : 0;
 }
 
 float NoiseBilateral::colorCloseness(int val1, int val2)
 {
-    qDebug() << Q_FUNC_INFO << "Not implemented yet!";
+    return exp( -(pow(val1 - val2, 2) / (2 * pow(sigma_r, 2))));
-
-    return 0;
 }
 
 float NoiseBilateral::spatialCloseness(QPoint point1, QPoint point2)
 {
-    qDebug() << Q_FUNC_INFO << "Not implemented yet!";
+    return exp(
-
+                -(pow(point1.x() - point2.x(), 2) + pow(point1.y() - point2.y(), 2))
-    return 0;
+                /
+                (2 * pow(sigma_d * 2, 2))
+              );
 }

src/core/transformations/noise_median.cpp

@@ -17,7 +17,14 @@ 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 r = getMedian(x,y, RChannel);
+                int g = getMedian(x,y, GChannel);
+                int b = getMedian(x,y, BChannel);
+                newImage->setPixel(x, y, QColor(r,g,b).rgb());
+            }
+        }
 
     return newImage;
 }
@@ -25,8 +32,29 @@ PNM* NoiseMedian::transform()
 int NoiseMedian::getMedian(int x, int y, Channel channel)
 {
     int radius = getParameter("radius").toInt();
+    radius = radius * 2 + 1;
 
-    qDebug() << Q_FUNC_INFO << "Not implemented yet!";
+    math::matrix<float> window = getWindow(x, y, radius, channel, RepeatEdge);
+        int table_size = radius * radius;
+        int table[table_size];
 
-    return 0;
+        int table_index = 0;
+
+        for (int x=0;x<radius;++x) {
+            for (int y=0;y<radius;++y) {
+                table[table_index] = window[x][y];
+                table_index++;
+            }
+        }
+
+        std::sort(table, table + (table_size - 1));
+
+        int median;
+
+        if (table_size % 2 != 0)
+            median = table[ table_size / 2 ];
+        else
+            median = (table[ (table_size - 1) / 2 ] + table[ table_size / 2 ]) / 2.0;
+
+        return median;
 }