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Vision-CW2/src/main/java/uk/ac/soton/ecs/ik1g19/hybridimages/App.java

 package uk.ac.soton.ecs.ik1g19.hybridimages;
 
+import jAudioFeatureExtractor.AudioFeatures.FeatureExtractor;
 import org.openimaj.image.DisplayUtilities;
 import org.openimaj.image.FImage;
 import org.openimaj.image.ImageUtilities;

Vision-CW2/src/main/java/uk/ac/soton/ecs/ik1g19/hybridimages/MyConvolution.java

@@ -6,6 +6,7 @@ import org.openimaj.image.processor.SinglebandImageProcessor;
 
 public class MyConvolution implements SinglebandImageProcessor<Float, FImage> {
 
+    //templated to be used during convolution
     private float[][] kernel;
 
 
@@ -15,14 +16,13 @@ public class MyConvolution implements SinglebandImageProcessor<Float, FImage> {
     }
 
 
-
+    /**
+     * @desc Perform template convolution on given image
+     * @param image Image to be transformed
+     */
     @Override
     public void processImage(FImage image) {
-        // convolve image with kernel and store result back in image
-        //
-        // hint: use FImage#internalAssign(FImage) to set the contents
-        // of your temporary buffer image to the image.
-
+        //temp image for writing values to during convolution
         FImage tmpImg = image.clone();
 
         //border size on left and right is half kernel width
@@ -42,8 +42,8 @@ public class MyConvolution implements SinglebandImageProcessor<Float, FImage> {
 
 
         //convolve template lol
-        for (int x = 0 - bLR; x < imgW - 1 - bLR; x++) { //all columns minus border
-            for (int y = 0 - bTB; y < imgH - 1 - bTB; y++) { //all rows minus border
+        for (int x = 0 - bLR; x < imgW - 1 - bLR; x++) { //traverse columns, start from zero padding
+            for (int y = 0 - bTB; y < imgH - 1 - bTB; y++) { //traverse rows, start from zero padding
                 float sum = 0f;
                 for (int kX = 0; kX < kW; kX++) { //all points in the kernel
                     for (int kY = 0; kY < kH; kY++) {
@@ -53,6 +53,7 @@ public class MyConvolution implements SinglebandImageProcessor<Float, FImage> {
                         //implicit zero-padding
                         boolean outbounds = (cX < 0) || (cX > imgW - 1) || (cY < 0) || (cY > imgH - 1);
 
+                        //zero padding will not affect sum
                         if (!outbounds) {
                             sum += image.getPixel(cX, cY) * //pixel value...
                                     kernel[kH - kY - 1][kW - kX - 1]; //multiplied with kernel value
@@ -63,6 +64,7 @@ public class MyConvolution implements SinglebandImageProcessor<Float, FImage> {
             }
         }
 
+        //replace original image with convolved image
         image.internalAssign(tmpImg);
     }
 

Vision-CW2/src/main/java/uk/ac/soton/ecs/ik1g19/hybridimages/MyHybridImages.java

@@ -4,6 +4,10 @@ import org.openimaj.image.DisplayUtilities;
 import org.openimaj.image.MBFImage;
 import org.openimaj.image.processing.convolution.Gaussian2D;
 
+
+/**
+ * @desc Combines low and high frequencies of two images to form a hybrid image
+ */
 public class MyHybridImages {
     /**
      * @desc Compute a hybrid image combining low-pass and high-pass filtered images
@@ -21,29 +25,30 @@ public class MyHybridImages {
      * @return the computed hybrid image
      */
     public static MBFImage makeHybrid(MBFImage lowImage, float lowSigma, MBFImage highImage, float highSigma) {
-        //implement your hybrid images functionality here.
-        //Your submitted code must contain this method, but you can add
-        //additional static methods or implement the functionality through
-        //instance methods on the `MyHybridImages` class of which you can create
-        //an instance of here if you so wish.
-        //Note that the input images are expected to have the same size, and the output
-        //image will also have the same height & width as the inputs.
-
+        //kernels for gaussian averaging
         float[][] lowGausK = Gaussian2D.createKernelImage(gSigmaToSize(lowSigma), lowSigma).pixels;
         float[][] highGausK = Gaussian2D.createKernelImage(gSigmaToSize(highSigma), highSigma).pixels;
 
+        //convolution operators for gaussian averaging
         MyConvolution gAvgLow = new MyConvolution(lowGausK);
         MyConvolution gAvgHigh = new MyConvolution(highGausK);
 
+        //lowpass on first image
         lowImage.processInplace(gAvgLow);
 
-        MBFImage tmpHigh = highImage.process(gAvgHigh);
-        highImage.subtractInplace(tmpHigh);
+        //high pass on second image
+        MBFImage tmpHigh = highImage.process(gAvgHigh); //lowpass...
+        highImage.subtractInplace(tmpHigh); //subtracted from original image
 
+        //combine frequencies
         return highImage.add(lowImage);
     }
 
 
-
+    /**
+     * @desc Helper function, find kernel size for given sigma
+     * @param sigma Given sigma value
+     * @return Appropriate kernel size
+     */
     private static int gSigmaToSize(float sigma) {int size = (int)(8.0f*sigma+1.0f); return size%2==0 ? size++ : size;}
 }
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