/**
* Applies the palette to <code>image</code> using the KdTree to find the nearest neighbor.
* Returned Image is a ColorImage. <code>image</code> is not modified.
*
* @param image ColorImage to apply palette to
* @return ColorImage
*/
protected Image apply(ColorImage image) {
RealColorImage realImage = ImageConverter.toRealColor(image);
ColorImage newImage = new ColorImage(realImage.X(), realImage.Y());
float[] total = null;
float[] best = null;
int[] temp = new int[3];
for (int x = 0; x < realImage.X(); x++) {
for (int y = 0; y < realImage.Y(); y++) {
tree2.getValues().removeAllElements();
do {
total = realImage.get(x, y);
tree2.findNearest(total, tree2.getRoot(), threshold);
threshold += 2;
} while (tree2.getValues().size() == 0);
threshold = 8;
if (tree2.getValues().size() != 1) best = findBest(total);
else best = (float[]) tree2.getValues().elementAt(0);
temp[0] = (int) best[0];
temp[1] = (int) best[1];
temp[2] = (int) best[2];
newImage.set(x, y, temp);
}
}
System.out.println("Done with the apply");
return newImage;
}
/** Utility methode for apply() */
private float[] findBest(float[] best) {
float dist = 999999;
float[] val = new float[3];
float tempDist = 0;
int location = 0;
if (exact != -999) return (float[]) tree2.getValues().elementAt(exact);
else {
for (int x = 0; x < tree2.getValues().size(); x++) {
val = (float[]) tree2.getValues().elementAt(x);
tempDist =
(((val[0] - best[0]) * (val[0] - best[0]))
+ ((val[1] - best[1]) * (val[1] - best[1]))
+ ((val[2] - best[2]) * (val[2] - best[2])));
if (tempDist <= dist) {
dist = tempDist;
location = x;
}
}
}
return (float[]) tree2.getValues().elementAt(location);
}
/**
* Creates a new instance of Nearest. Note, this function uses a KdTree which is calculated in
* this constructor.
*
* @see KdTree
*/
public Nearest(RealColorImage paletteImage) {
tree2 = new KdTree(3);
tree2.buildTreePalette(paletteImage);
}